Browse 12,955 Workflows

By Mauricio Perera

📁 Analyze uploaded images, videos, audio, and documents with specialized tools — powered by a lightweight language-only agent. 🧭 What It Does This workflow enables multimodal file analysis using Google Gemini tools connected to a text-only LLM agent. Users can upload images, videos, audio files, or documents via a chat interface. The workflow will: Upload each file to Google Gemini and obtain an accessible URL. Dynamically generate contextual prompts based on the file(s) and user message. Allow the agent to invoke Gemini tools for specific media types as needed. Return a concise, helpful response based on the analysis. 🚀 Use Cases Customer support**: Let users upload screenshots, documents, or recordings and get helpful insights or summaries. Multimedia QA**: Review visual, audio, or video content for correctness or compliance. Educational agents**: Interpret content from PDFs, diagrams, or audio recordings on the fly. Low-cost multimodal assistants: Achieve multimodal functionality **without relying on large vision-language models. 🎯 Why This Architecture Matters Unlike end-to-end multimodal LLMs (like Gemini 1.5 or GPT-4o), this template: Uses a text-only LLM (Qwen 32B via Groq) for reasoning. Delegates media analysis to specialized Gemini tools. ✅ Advantages | Feature | Benefit | | ----------------------- | --------------------------------------------------------------------- | | 🧩 Modular | LLM + Tools are decoupled; can update them independently | | 💸 Cost-Efficient | No need to pay for full multimodal models; only use tools when needed | | 🔧 Tool-based Reasoning | Agent invokes tools on demand, just like OpenAI’s Toolformer setup | | ⚡ Fast | Groq LLMs offer ultra-fast responses with low latency | | 📚 Memory | Includes context buffer for multi-turn chats (15 messages) | 🧪 How It Works 🔹 Input via Chat Users submit a message and (optionally) files via the chatTrigger. 🔹 File Handling If no files: prompt is passed directly to the agent. If files are included: Files are split, uploaded to Gemini (to get public URLs). Metadata (name, type, URL) is collected and embedded into the prompt. 🔹 Prompt Construction A new chatInput is dynamically generated: User message Media: [array of file data] 🔹 Agent Reasoning The Langchain Agent receives: The enriched prompt File URLs Memory context (15 turns) Access to 4 Gemini tools: IMG: analyze image VIDEO: analyze video AUDIO: analyze audio DOCUMENT: analyze document The agent autonomously decides whether and how to use tools, then responds with concise output. 🧱 Nodes & Services | Category | Node / Tool | Purpose | | --------------- | ---------------------------- | ------------------------------------- | | Chat Input | chatTrigger | User interface with file support | | File Processing | splitOut, splitInBatches | Process each uploaded file | | Upload | googleGemini | Uploads each file to Gemini, gets URL | | Metadata | set, aggregate | Builds structured file info | | AI Agent | Langchain Agent | Receives context + file data | | Tools | googleGeminiTool | Analyze media with Gemini | | LLM | lmChatGroq (Qwen 32B) | Text reasoning, high-speed | | Memory | memoryBufferWindow | Maintains session context | ⚙️ Setup Instructions 1. 🔑 Required Credentials Groq API key** (for Qwen 32B model) Google Gemini API key** (Palm / Gemini 1.5 tools) 2. 🧩 Nodes That Need Setup Replace existing credentials on: Upload a file Each GeminiTool (IMG, VIDEO, AUDIO, DOCUMENT) lmChatGroq 3. ⚠️ File Size & Format Considerations Some Gemini tools have file size or format restrictions. You may add validation nodes before uploading if needed. 🛠️ Optional Improvements Add logging and error handling (e.g., for upload failures). Add MIME-type filtering to choose the right tool explicitly. Extend to include OCR or transcription services pre-analysis. Integrate with Slack, Telegram, or WhatsApp for chat delivery. 🧪 Example Use Case > "Hola, ¿qué dice este PDF?" Uploads a document → Agent routes it to Gemini DOCUMENT tool → Receives extracted content → LLM summarizes it in Spanish. 🧰 Tags multimodal, agent, langchain, groq, gemini, image analysis, audio analysis, document parsing, video analysis, file uploader, chat assistant, LLM tools, memory, AI tools 📂 Files This template is ready to use as-is in n8n. No external webhooks or integrations required. An n8n automation workflow template by Mauricio Perera.

By Robert Breen

This n8n workflow scrapes recent Instagram posts by hashtag and generates new, relevant caption ideas using OpenAI. It avoids making up suggestions by analyzing real-world content and surfacing common patterns. ✅ Use Case Marketing teams, content creators, or social media managers can: Discover what’s trending for a specific topic Automatically generate Instagram captions based on real posts Understand common caption styles for a niche Save time brainstorming ideas while staying on-brand 🧠 How It Works 1️⃣ Manual Trigger 🧩 Node: When clicking ‘Execute workflow’ Manually starts the workflow for testing or single-run execution. 2️⃣ Define the Hashtag 🧩 Node: Create Search Term Sets the value of the hashtag you'd like to scan. Default is n8n, but you can modify it to anything. { "Search_Term": "yourCustomHashtag" } 3️⃣ Scrape Instagram Posts 🧩 Node: Find Recent Posts API**: Apify Instagram Hashtag Scraper Setup**: Visit Apify Console Create an API token In n8n, go to Credentials and add HTTP Query Auth Use ?token=yourTokenHere as the query string JSON Body: { "hashtags": ["{{ $json.Search_Term }}"], "resultsLimit": 20, "resultsType": "posts" } 4️⃣ Extract Captions 🧩 Node: Set bio and follower count Extracts just the caption from each post and stores it in a clean variable for the AI agent to use. 5️⃣ Aggregate Captions 🧩 Node: Aggregate Gathers all captions into one list before processing. Useful for passing a large text block into the AI. 6️⃣ Convert to Single Text Block 🧩 Node: Convert table names and columns into single text for agent Uses a Code node to combine all captions into a single string for OpenAI to read: return [ { json: { text: items .map(item => - ${JSON.stringify(item.json)}) .join('\n\n'), }, }, ]; 7️⃣ Generate Caption Ideas with AI 🧩 Node: AI Agent Takes the combined post text and sends it to GPT-4o-mini. Includes this system message: I'm looking for ideas for posts about {{ $('Create Search Term').item.json.Search_Term }}. Here’s the last 5 posts on Instagram about the topic. Use those to help me generate a list of relevant captions. Do not make up ideas that are not like the others in the list. Output like this: { "Post Idea": ["Idea1", "Idea2"], "Most Common Post": ["common post 1", "common post 2"] } 8️⃣ Choose Language Model 🧩 Node: OpenAI Chat Model Model**: gpt-4o-mini Credential**: Use your OpenAI API key. Get it from: OpenAI API Keys Add it in n8n under OpenAI credentials. 9️⃣ Parse the AI Output 🧩 Node: Structured Output Parser Parses the GPT response into structured JSON: { "Post Idea": ["Idea1", "Idea2"], "Most Common Post": ["common post 1", "common post 2"] } 🔟 Split the Outputs 🧩 Nodes: Split Out, Split Out1 Separates the Post Idea list and Most Common Post list into individual items. 🔁 Merge for Final Output 🧩 Node: Merge Combines the two split lists into one output stream. 👤 Need More Help? Robert Breen Automation Consultant | AI Workflow Designer | n8n Expert 📧 robert@ynteractive.com 🔗 LinkedIn. An n8n automation workflow template by Robert Breen.

By iamvaar

Title: ⚙️ Deep Dive: Automating Weekly US Trademark Reports with n8n, RapidAPI & Google Drive (No-Code Workflow) Full Breakdown Post: In this in-depth walkthrough, we're exploring a powerful no-code automation built entirely using n8n, that automatically fetches the latest US trademark registrations every 7 days, saves them to a CSV, and uploads that file to your Google Drive — no manual effort required. Whether you're a startup founder, legal tech builder, or data analyst, this type of automation can save you hours every week and give you a real-time pulse on newly registered trademarks in the US. ⚙️ What This Workflow Does: Every week, the workflow automatically: Triggers on a schedule Calculates the date range (today and 7 days prior) Fetches trademark data from the USPTO via a RapidAPI endpoint Splits the API response into individual rows Converts it into a CSV file Uploads the file to Google Drive with a dynamic name like: Active TM (2025-07-29 - 2025-08-05).csv 🔍 Node-by-Node Breakdown 1. Schedule Trigger Node**: Schedule Trigger Purpose**: Starts the workflow every 7 days 2. Date & Time Node**: Date & Time Purpose**: Captures the current timestamp in ISO format to use for calculations. 3. Manual (Set Start & End Dates) Node**: Set Purpose**: Assigns two dynamic values: Start_Date: Current date minus 7 days End_Date: Current date (today) 4. HTTP Request: Get Trademark Data Node**: HTTP Request Method**: POST This returns an array of trademark records from USPTO's database that were registered in the past week. 5. Split the Array into Items Node**: Code This takes the results array from the HTTP response and flattens it so that each trademark record becomes its own item in n8n's context. 6. Convert to CSV File Node**: Convert to File File Name**: test.csv (you can change this dynamically if needed) This node takes all the individual trademark JSON objects and generates a CSV file out of them. 7. Upload to Google Drive Node**: Google Drive Folder ID**: Your target folder’s ID Dynamic Name**: =Active TM ({{ $('Manual').item.json.Start_Date }} - {{ $('Manual').item.json.End_Date }}) This uploads the generated CSV file directly into your specified Google Drive folder with the correct name and date range. 🧠 Why This is Powerful Zero maintenance** once configured Always fresh** trademark data weekly Ideal for market research, brand monitoring, IP tracking Fully serverless... all you need is n8n, a RapidAPI key, and Google Drive access 🛡️ Disclaimer > DISCLAIMER: THIS IS FOR EDUCATIONAL PURPOSES ONLY. THE CREATOR IS NOT LIABLE FOR ANY LOSSES OR DAMAGES CAUSED BY MISUSE OF THIS WORKFLOW. 🚀 Final Thoughts With this one workflow, you're building a production-grade automation pipeline that would otherwise take a full dev sprint to manually script and deploy. Use it, extend it, and plug it into other workflows like: Auto-emailing the report Pushing to Google Sheets Generating insights via AI n8n is your playground — this is just the beginning. An n8n automation workflow template by iamvaar.

By mariskarthick

QuantumDefender AI is a next-generation intelligent cybersecurity assistant designed to harness the symbolic strength of quantum computing’s promise alongside cutting-edge AI capabilities. This sophisticated agent empowers SOC analysts, red teamers, and security researchers with rapid threat investigation, operational automation, and intelligent command execution—all driven by GPT-4 and integrated tools, accessible through Telegram or on any medium. 🔑 Key Features: Expert-Level Cybersecurity Research & Analysis: Leverages powerful AI models to deliver clean, detailed, domain-specific insights across detection, remediation, and offensive security. Command & Control: Executes Linux shell commands, autonomous scripts, and system operations securely in isolated environments. Real-Time Web Intelligence: Utilizes integrated Langsearch API to provide timely internet research with contextual relevance. Calendar & Scheduling Automation: Manage Google Calendar events or any similar application(create, update, delete, retrieve) dynamically from chat. Multi-Tool Orchestration: Combines calculator functions, internet searches, command execution, and messaging for comprehensive operational support. Telegram-native Chatbot: Delivers an adaptive, memory-informed, and interactive conversational experience with immediate typing indicators and high responsiveness. Conversation & Session Management: Maintains context-aware, session-based memory to enable smooth, multi-turn dialogues with individual users. Sends “typing…” indicators during processing to ensure an interactive, user-friendly chat experience. Operates exclusively within Telegram, delivering rich, timely responses and leveraging all Telegram bot capabilities. Execution Intelligence & Safety: Fully autonomous in deciding which tools to invoke, how frequently, and in what sequence to fulfill user requests comprehensively and responsibly. Operates within a secure temporary folder environment to contain all command executions safely and avoid persistent or harmful side effects. Enforces strict safety protocols to avoid running malicious or destructive commands, maintaining ethical standards and compliance. Use Cases: Cybersecurity researchers and operators seeking an intelligent assistant to accelerate investigations and automate routine tasks. Red team professionals requiring on-the-fly command execution and information gathering integrated with tactical chat interactions. SOC teams aiming to augment their alert triage and incident handling workflows with AI-powered analysis and action. Anyone looking for a robust multi-tool AI chatbot integrated with real-world operational capabilities. Setup Requirements: OpenAI API key for GPT-4.1-nano language processing. Telegram Bot API credentials with proper webhook setup to receive and respond to messages. Google OAuth credentials for Calendar integration if calendar features are used. SSH access credentials for executing commands on remote hosts, if remote execution is enabled. Internet connectivity for the Langsearch web search API. Customization & Extensibility: The workflow is built modularly with n8n’s flexible node system. Users can extend it by adding more tools, integrating other services (ticketing, threat intel, scanning tools), or modifying interaction logic to suit specialized operational needs and environments. Created by Mariskarthick M Senior Security Analyst | Detection Engineer | Threat Hunter | Open-Source Enthusiast. An n8n automation workflow template by mariskarthick.

By mariskarthick

Reduce human delays between malware detection and remediation in MSSP/SOC environments. This workflow automates full endpoint antivirus scanning immediately after high-severity endpoint infection wazuh alerts, closing the gap between alerting and action. Why Use This Workflow? Malware alerts are only effective if acted upon swiftly. Manual follow-ups are slow or often missed, letting threats persist. Automates detection, triage, scan initiation, and notification—all within one minute of alerting. Ensures consistent, auditable actions across endpoints running Linux or Windows. 🔑 Key Features Listens for high-severity Wazuh AV infection alerts (e.g., rule 52502). Uses GPT-4 for AI-powered alert summaries to speed triage and decision making. Extracts exact infected file paths using AI and regex for targeted scanning. Runs ClamAV/defender scans directly on endpoints via SSH with least-privilege credentials. Sends real-time scan results and remediation updates through Telegram, Slack, or email. Runs locally with limited permissions—no need for elevated Wazuh manager access. 🎯 Impact Eliminates manual lag—scans start automatically and immediately. Standardizes response playbooks for reliable, repeatable remediation. Reduces threat dwell time, minimizing risk exposure. Provides full event-to-remediation visibility via logs and notifications. 🚀 Get Started Configure Wazuh Manager to forward AV alerts to this n8n webhook. Import this workflow JSON into your n8n instance. Set up required credentials: OpenAI API, SSH access for ClamAV scanning, notification channels (Telegram/Slack/email). Activate the workflow and monitor alerts triggering automated scans and reports. 📂 Enjoy customizing Swap ClamAV with your preferred antivirus commands (e.g., Defender) as needed. Integrate with your existing communication or ticketing systems. Extend or adapt for multi-endpoint orchestration or other alert rules. Created by Mariskarthick M Senior Security Analyst | Detection Engineer | Threat Hunter | Open-Source Enthusiast. An n8n automation workflow template by mariskarthick.

By John Pranay Kumar Reddy

✨ Summary Efficiently monitor Kubernetes environments by sending only unique error logs from Grafana Loki to Slack. Reduces alert fatigue while keeping your team informed about critical log events. 🧑‍💻 Who’s it for DevOps or SRE engineers running EKS/GKE/AKS Anyone using Grafana Loki and Promtail for centralized logging Teams that want Slack alerts but hate alert spam 🔍 What it does This n8n workflow queries your Loki logs every 5 minutes, filters only the critical ones (error, timeout, exception, etc.), removes duplicate alerts within the batch, and sends clean alerts to a Slack channel with full metadata (pod, namespace, node, container, log, timestamp). 🧠 How it works 🕒 Schedule Trigger Every 5 minutes (customizable) 🌐 Loki HTTP Query Pulls logs from the last 10 minutes Keyword match: error, failed, oom, etc. 🧹 Log Parsing Extracts log fields (pod, container, etc.) Skips empty/malformed results 🧠 Deduplication Removes repeated error messages (within query window) 📤 Slack Notification Sends nicely formatted message to Slack ⚙️ Requirements Tool Notes Loki- Exposed internally or externally Slack App- With chat:write OAuth n8n- Cloud or self-hosted 🔧 How to Set It Up Import the JSON file into n8n Update: Loki API URL (e.g., http://loki-gateway.monitoring.svc.cluster.local) Slack Bearer Token (via credentials) Target Slack channel (e.g., #k8s-alerts) (Optional) Change keywords in the query regex Activate the workflow Ensure n8n pod/container is having access to your kubernetes cluster/pods/namespaces 🛠 How to Customize Want more or fewer keywords? Adjust the regex in the Query Loki for Error Logs node. Need to increase deduplication logic? Enhance the Remove Duplicate Alerts node. Want 5-log summaries every 5 min? Fork this and add a Batch + Slack group sender. Grafana Loki logs to Slack Output. An n8n automation workflow template by John Pranay Kumar Reddy.

By Anna Bui

🎯 Universal Meeting Transcript to LinkedIn Content Automatically transform your meeting insights into engaging LinkedIn content with AI Perfect for coaches, consultants, sales professionals, and content creators who want to share valuable insights from their meetings without the manual effort of content creation. How it works Calendar trigger detects when your coaching/meeting ends Waits for meeting completion, then sends you a form via email You provide the meeting transcript and specify post preferences AI analyzes the transcript using your personal brand guidelines Generates professional LinkedIn content based on real insights Creates organized Google Docs with both transcript and final post Sends you links to review and publish your content How to use Connect your Google Calendar and Gmail accounts Update the calendar filter to match your meeting types Customize the AI prompts with your brand voice and style Replace email addresses with your own Test with a sample meeting transcript Requirements Google Calendar (for meeting detection) Gmail (for form delivery and notifications) Google Drive & Docs (for content storage) LangChain AI nodes (for content generation) Good to know AI processing may incur costs based on your LangChain provider Works with any meeting platform - just copy/paste transcripts Can be adapted to use webhooks from recording tools like Fireflies.ai Memory nodes store your brand guidelines for consistent output Happy Content Creating!. An n8n automation workflow template by Anna Bui.

By Robert Breen

This no-code n8n workflow finds recent Instagram posts by hashtag, scrapes profile data, and uses an AI agent to evaluate whether each account is a good collaboration lead. The workflow filters based on the number of followers and the content of their bio, and outputs structured reasoning for outreach decisions. Perfect for creators, marketers, or business developers looking to automate influencer or community partnership prospecting—especially in niche ecosystems like n8n. ✅ Key Features 🔍 Hashtag Discovery**: Finds recent Instagram posts from a specified hashtag (e.g., #n8n) 👤 Account Scraping**: Retrieves profile details such as follower count and biography 🧠 AI Evaluation**: Uses OpenAI and LangChain to determine if the profile is a good fit for outreach 📦 Structured Output**: Returns a JSON object with "Yes/No" lead status and reasoning 🛠️ Manual Execution**: Run on demand using the manual trigger 🧰 What You'll Need | Tool / API | Purpose | Setup Steps | |-------------------------|------------------------------------------|-------------| | Apify Account | To access Instagram scraping actors | Create account → Generate API Token → Use in httpQueryAuth credential in n8n | | OpenAI API Key | To power the AI decision-making agent | Sign up at OpenAI → Create API key → Paste into OpenAI credential in n8n | | LangChain Plugin for n8n | AI Orchestration with System Message | Install LangChain nodes from Community Nodes (already installed in this workflow) | 🔧 Step-by-Step Setup 1️⃣ Manual Trigger Node**: When clicking ‘Execute workflow’ Use**: Allows you to run the workflow manually while testing. 2️⃣ Define Hashtag Node**: Create Search Term Value**: Sets "n8n" as the default Instagram hashtag to scan. You can edit this to any other hashtag you'd like. 3️⃣ Find Recent Posts Node**: Find Recent Posts API**: Apify Instagram Hashtag Scraper Auth Setup**: Go to your Apify Console Click “Create new token” In n8n, create a new HTTP Query Auth credential Set token in the token query param (e.g., ?token=yourTokenHere) Choose the credential in this node 4️⃣ Scrape Each Profile Node**: Scrape Accounts API**: Apify Instagram Profile Scraper Body**: JSON with usernames from the hashtag search Note**: Uses the same httpQueryAuth credential as the previous node. 5️⃣ Extract Fields Node**: Set bio and follower count What it does**: Extracts biography and followersCount from the profile JSON and stores them in clean variables for AI input. 6️⃣ AI Lead Scoring Node**: AI Agent Purpose**: Uses GPT-4o-mini to analyze the bio and follower count Prompt Details**: 7️⃣ AI Model Node**: OpenAI Chat Model Model**: gpt-4o-mini Credential**: Connect your OpenAI account via API Key. Go to OpenAI API Keys Copy your key and create a new OpenAI API credential in n8n. 8️⃣ Output Parser Node**: Structured Output Parser What it does**: Parses the response from the AI into structured JSON for further use (e.g., storing leads, sending to Airtable, etc.) 🧪 Sample Output { "lead status": "Yes", "Reasoning": "The user has 3.5k followers and their bio shows they build automations with n8n." } 📬 Need More Help? If you'd like assistance setting this up, customizing it to your niche, or expanding it to score and store leads automatically — I can help! 👤 Robert Breen Automation Consultant | AI Workflow Designer | n8n Expert 📧 robert@ynteractive.com 🌐 ynteractive.com 🔗 LinkedIn. An n8n automation workflow template by Robert Breen.

By Luis Hernandez

GLPI Pending Tickets Notification to Microsoft Teams 📋 Overview Automate daily notifications for pending GLPI tickets directly to Microsoft Teams. Never miss critical support cases with this workflow that monitors assigned tickets and sends personal alerts. 🔧 How It Works Connect to GLPI - Authenticates and searches for your assigned tickets Filter Results - Finds tickets in "In Progress" status within your entity Send Notifications - Delivers formatted alerts to your Teams chat Clean Up - Properly closes GLPI session for security 📊 What Gets Monitored Tickets assigned to specific technician (configurable) Status: "In Progress/Assigned" Entity: Your organization (customizable) Date range: Tickets after specified date ⚡ Key Benefits Never Miss Deadlines - Daily automated reminders Personal Focus - Only your assigned tickets Time Savings - Eliminates manual checking (15-30 min daily) Rich Details - Shows ticket title, ID, and due date ⚙️ Setup Steps Time Required: ~30 minutes Import Template - Add workflow to your n8n instance Configure GLPI - Set server URL, credentials, and app token Set Technician ID - Update to your GLPI user ID Connect Teams - Link your Microsoft Teams account Customize Filters - Adjust entity name and date range Test & Schedule - Verify notifications and set daily trigger 🎨 Easy Customization Change technician ID for different users Adjust notification schedule (default: 8 AM daily) Modify entity filters for your organization Add multiple technicians by duplicating workflow 📋 Prerequisites GLPI instance with API enabled GLPI user account with ticket read permissions Microsoft Teams account (basic license) n8n with Microsoft Teams integration Perfect for support technicians who want automated reminders about their pending GLPI tickets without manual daily checks. An n8n automation workflow template by Luis Hernandez.

By WeWeb

This n8n template helps you build a full AI-powered LinkedIn content generator with just a few clicks. Paired with the free WeWeb UI template, it becomes a ready-to-use web app where users can: Add their own OpenAI API key Customize the prompt and define 6 content topics Edit the AI-generated topics Choose when to generate LinkedIn posts, complete with hashtags and an optional image Who This Is For Perfect for marketers, indie hackers, and solopreneurs who want to build their personal brand on LinkedIn while staying in control of what gets posted. 🧠 What Makes This Different Unlike most AI agents, you stay fully in control: You define the tone and focus via the prompt. You choose which topics to keep or modify. You decide when to generate a post. You can build on top of this and create your own SaaS product. It’s also modular and extendable—hook it up to your backend, add user login, or feed AI improvements based on user input. ⚙️ How It Works Triggering Events: The app includes 3 pre-configured triggers, ready to be hooked into your WeWeb frontend. Just update the webhook URLs after duplicating the n8n workflow. Topic Generation: A call is made to OpenAI (GPT-4) to generate topic ideas based on your prompt. Post Creation: Once topics are approved or edited, GPT-4 writes full posts with suggested hashtags. Image Generation (Optional): If enabled, a DALL·E call generates a relevant image. Everything Stays Local: All data and images are handled locally, no cloud storage setup needed. 🧪 Requirements & Setup No fancy infrastructure required. Here’s what helps you get started: Free WeWeb account** (recommended) to use the frontend UI template OpenAI account** with API access (for GPT-4 and DALL·E) n8n account** (self-hosted or cloud) to run the backend workflow The template is completely free to use. Since each user adds their own OpenAI API key, you don't need to worry about usage costs or rate limits on your end. 🔧 Want to Go Further? This setup is beginner-friendly, but developers can: Add user accounts Save post history Feed user feedback back into the prompt logic Launch their own branded version as a SaaS. An n8n automation workflow template by WeWeb.

By Luan Correia

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This comprehensive RAG workflow enables your AI agents to answer user questions with contextual knowledge pulled from your own documents — using metadata-rich embeddings stored in Supabase. 🔧 Key Features: RAG Agents powered by GPT-4.5 or GPT-3.5 via OpenRouter or OpenAI. Supabase Vector Store to store and retrieve document embeddings. Cohere Reranker to improve response relevance and quality. Metadata Agent to enrich vectorized data before ingestion. PDF Extraction Flow to automatically parse and upload documents with metadata. ✅ Setup Steps: Connect your Supabase Vector Store. Use OpenAI Embeddings (e.g. text-embedding-3-small). Add API keys for OpenAI and/or OpenRouter. Connect a reranker like Cohere. Process documents with metadata before embedding. Start chatting — your AI agent now returns context-rich answers from your own knowledge base! Perfect for building AI assistants that can reason, search and answer based on internal company data, academic papers, support docs, or personal notes. An n8n automation workflow template by Luan Correia.

By Muhammad Bello

Email Inbox Manager System Categories Email Automation AI-Powered Operations Internal Productivity Tools This workflow builds a fully automated AI-powered email categorization and response assistant. It intelligently processes, categorizes, labels, and drafts replies to incoming Gmail messages in real time using AI with zero manual involvement. Perfect for support, sales, finance, and internal operations. Benefits Automated Email Triage** – Every unread email is instantly read, analyzed, and classified AI-Powered Categorization** – Uses GPT-4 to understand content and apply correct labels Smart Response Generation** – Automatically drafts accurate replies based on category Slack Notifications** – Instantly notifies your team about internal or sales-related messages Seamless Gmail Integration** – Labels, drafts, and marks emails directly in your inbox Custom Classification Rules** – Tailored to internal, support, sales, finance, and promotional needs How It Works Gmail Trigger: Monitors Gmail inbox in real-time for new unread messages Triggers the workflow every minute with no need for manual refresh Smart Classification: Feeds email body to AI-powered Text Classifier Categories include: Internal, Customer Support, Promotions, Admin/Finance, and Sales Opportunity Classification based on sender domain, keywords, and context AI-Based Labeling: Applies appropriate Gmail label based on classification result Helps keep inbox clean, organized, and easily searchable AI Reply Generation: Specialized GPT-4 agents generate replies tailored to each category: Internal:** Polished team replies Customer Support:** Clear and professional customer responses Promotions:** Summarizes and evaluates promotional value Admin/Finance:** Extracts invoice/payment information Sales Opportunity:** Drafts personalized replies and sales notifications Auto-Drafting + Slack Alerts: Replies are saved as Gmail drafts, ready for review or direct send Sends Slack notifications for Internal or Sales Opportunities Includes subject lines and quick message previews Smart Decision-Making: Promotional emails are evaluated with AI for usefulness Only valuable offers are flagged or responded to Automatically marks emails as read after processing Business Use Cases Customer Support Teams** – Automatically categorize and prep replies to client messages Sales Reps** – Instantly receive drafted responses to new inquiries Operations Managers** – Keep internal comms clear and responsive Finance Departments** – Auto-extract and review payment/invoice messages Founders** – Never miss an important email while your AI sorts and replies for you Difficulty Level: Intermediate Estimated Build Time: 2–4 hours Monthly Operating Cost: $20–80 (depending on OpenAI usage and Slack volume) Required Setup Gmail Integration Set up Gmail OAuth2 connection Create labels: Internal, Customer Support, Promotions, Admin/Finance, Sales Opportunity OpenAI Integration Connect GPT-4 or GPT-4o account Configure role-based prompts for each email category Output structured response data (subject, body, notification) Slack Integration Set up Slack OAuth2 connection Configure target Slack channel Notify team when important categories are triggered System Architecture The workflow follows a powerful 6-stage automation: Trigger – Poll Gmail for new unread emails Classify – AI categorizes the email into the right bucket Label – Applies Gmail label for search and visibility Generate Reply – GPT-4 crafts draft email reply Draft Email – Saves response in Gmail Notify – Optional Slack message alerts for priority emails Why This System Works Inbox Clarity – Keeps your inbox categorized and organized Human Quality Replies – AI-generated messages sound professional and personalized Time-Saving Automation – Handles support, sales, internal ops, and finance without touching your inbox Multi-Agent Architecture – Each email type is handled by a specialized GPT-4 prompt Real Time Reactions – From email receipt to Slack notification in under a minute. An n8n automation workflow template by Muhammad Bello.

By Punit

This n8n workflow automates the process of generating and publishing LinkedIn posts that align with your personal brand tone and trending tech topics. It uses OpenAI to create engaging content and matching visuals, posts it directly to LinkedIn, and sends a confirmation via Telegram with post details. 🔑 Key Features 🏷️ Random Hashtag Selection Picks a trending tag from a custom list for post inspiration. ✍️ AI-Generated Content GPT-4o crafts a LinkedIn-optimized post in your personal writing style. 🖼️ Custom Image Generation Uses OpenAI to generate a relevant image for visual appeal. 📤 Direct LinkedIn Publishing Posts are made automatically to your profile with public visibility. 📩 Telegram Notification You get a real-time Telegram alert with the post URL, tag, and timestamp. 📚 Writing Style Alignment Past posts are injected as examples to maintain a consistent tone. Ideal Use Case: Automate your daily or weekly LinkedIn presence with minimal manual effort while maintaining high-quality, relevant, and visually engaging posts. An n8n automation workflow template by Punit.

By Shiva

This workflow enables users to submit food images to a Telegram bot, which uses OpenAI’s GPT-4 Vision to identify the item and estimate its caloric value. The results are stored in Google Sheets and sent back to the user. What it does: Triggers on a photo sent via Telegram. Acknowledges the user with a sticky note message. Downloads the image file securely using Telegram's API. Sends the image to GPT-4 Vision with a prompt: “Describe this food and estimate its calories.” Logs the GPT response to a Google Sheet (with timestamp). Replies to the user with the result (e.g., food name and estimated calories). Use cases: Personal food tracking Nutrition logging via chat Meal journaling for fitness or health Requirements: Telegram Bot Token (via credentials) OpenAI GPT-4 Vision access Google Sheets credential with access to the target sheet Notes: You can extend this template to calculate daily totals, categorize meals (breakfast/lunch/dinner), or even integrate with calorie goals. The sticky note node confirms receipt to enhance UX. Ideal for wellness apps, chat-based food journals, or AI-powered health bots. An n8n automation workflow template by Shiva.

By Janak Patel

Use this template if you’re collecting leads in Google Sheets manually or automatically and need to send them emails daily using any personal or professional email provider. It’s simple yet effective. I’ve kept it easy so that anyone without technical or coding knowledge can still automate their emails and achieve excellent ROI. Setting up the workflow takes only 15 minutes. How it works: We connect Google Sheets with n8n to automatically fetch lead data. Google Sheets is used because it’s easy and widely accessible. Then, n8n sends emails daily at your scheduled times to the respective email addresses, using the subject lines and body text you've configured. It also verifies emails before sending. It checks email availability, deliverability, and updates the Google Sheet/CRM with the respective fields. Requirements: A Google Sheet/Excel/CRM tools with leads (A sample Google Sheet link is provided in the template) A working email account with SMTP information (SMTP info for the top 10 email providers is provided in the template) API key from any email verification tool (We use the Hunter API key in our use case. You can find the link in the template.) Setup Steps: You need a Google Sheet where you're collecting leads. You can replace Google Sheets with your CRM tool. Connect it using your credentials. Replace the manual trigger with a scheduled trigger to automate emails at your preferred time. Replace the email verification tool/Hunter API with your own API key. Add your SMTP credentials to connect the template with your preferred email provider. Using SMTP, you can send emails through Gmail, Outlook, Zoho, or any similar provider. This makes sending emails simple and cost-efficient. Note: SMTP, which stands for Simple Mail Transfer Protocol, is a communication protocol used to send email messages between mail servers. After sending the email, we update the Google Sheet with “Sent”; hence, the email is not sent again the next day. An n8n automation workflow template by Janak Patel.

By Oneclick AI Squad

This n8n workflow automatically tracks assignment deadlines and sends reminders to students and teachers. It checks for upcoming assignments daily, organizes the data, and sends email notifications to ensure deadlines are met. Good to Know Fully Automated**: Runs daily at 9 AM on weekdays to check assignments. Regular Updates**: Sends reminders for upcoming deadlines. Clear Notifications**: Emails a list of assignments to students and teachers. Error Handling**: Skips execution if no assignments are due. Scalable**: Works for multiple assignments and users. How It Works Reminder and Tracking Flow Set Schedule for Trigger: Starts the workflow daily at 9 AM on weekdays. Get Assignments: Retrieves assignment data from Notion database. IF Assignments Exist: Checks if there are any upcoming assignments. Split Items: Breaks down the assignment list for individual processing. Send Email Reminder: Emails reminders to students and teachers. No Assignments: Stops the workflow if no assignments are found. Example Database Columns Assignment ID**: Unique identifier for each assignment. Title**: Name of the assignment. Due Date**: Deadline for submission. Student ID**: Unique identifier for the student. Teacher ID**: Unique identifier for the teacher. Status**: Current status (e.g., Pending, Completed). How to Use Import Workflow: Add the workflow to n8n using the “Import Workflow” option. Set Up Notion: Configure n8n with Notion API credentials to fetch assignments. Configure Email: Add student and teacher email addresses and set up an email service (e.g., Gmail). Activate Workflow: Save and turn on the workflow in n8n. Check Logs: Verify reminders are sent and tracked. Requirements n8n Instance**: Self-hosted or cloud-based n8n setup. Notion Database**: API access with assignment data. Email Service**: SMTP setup (e.g., Gmail) for sending reminders. Admin Oversight**: Someone to monitor and adjust as needed. Customizing This Workflow Change Schedule**: Adjust the trigger to run at a different time or frequency. Add More Data**: Include additional fields like priority or notes. Custom Email**: Modify the email template for specific details. An n8n automation workflow template by Oneclick AI Squad.

By Oneclick AI Squad

This n8n workflow automatically creates and sends regular performance summaries to parents using data from a Learning Management System (LMS). It pulls student grades and attendance, formats them into easy-to-read reports, and emails them without any manual work. Good to Know Fully Automated**: Generates reports and sends emails using LMS data. Regular Updates**: Sends summaries on a set schedule (e.g., every Monday at 9 AM). Clear Reports**: Includes student grades, attendance, and progress notes. Error Alerts**: Notifies admins via email if something goes wrong. Scalable**: Works for multiple students across different classes. How It Works Report Generation Flow Weekly Trigger: Starts the process every Monday at 9 AM. Fetch LMS Data: Pulls grades, attendance, and progress from the LMS. Process Data: Organizes the data into a clear report format. Generate HTML Report: Creates a readable report with student details. Send Email to Parents: Emails the report to parents’ addresses. Log Report Delivery: Records the sent reports in a log. Example Sheet Columns Student ID**: Unique identifier for each student. Name**: Full name of the student. Grade**: Current academic grade or score. Attendance**: Percentage of classes attended. Progress Notes**: Brief comments on performance. Report Date**: Date the report was generated. How to Use Import Workflow: Add the workflow to n8n using the “Import Workflow” option. Set Up LMS Access: Configure n8n with LMS credentials to fetch data. Configure Email: Add parent email addresses and set up an email service (e.g., Gmail). Activate Workflow: Save and turn on the workflow in n8n. Check Logs: Verify reports are sent and logs are updated. Requirements n8n Instance**: Self-hosted or cloud-based n8n setup. LMS Access**: API or credentials to connect to the LMS. Email Service**: SMTP setup (e.g., Gmail) for sending reports. Admin Oversight**: Someone to monitor and fix any errors. Customizing This Workflow Change Schedule**: Adjust the trigger to send reports weekly or monthly. Add More Data**: Include extra LMS fields like behavior notes. Custom Email**: Change the email template for a personalized touch. An n8n automation workflow template by Oneclick AI Squad.

By WeblineIndia

Daily Weather Reports with OpenWeather API, Google Sheets, and Gmail This workflow fetches real-time weather data from the OpenWeather API, stores it in a Google Sheet, formats it into a beautifully styled HTML report and emails it to recipients automatically every day at 10:00 AM. It helps teams track and monitor daily weather trends and optionally correlate them with energy production or field operations. Who’s it for? Renewable energy teams monitoring solar/wind energy output vs weather Facility or operations managers requiring daily climate updates Researchers or analysts logging environmental metrics Any team needing automated, daily weather reports by email How it works? The workflow begins with a Schedule Trigger set to run at 10:00 AM IST daily. It calls the OpenWeather API to fetch weather metrics for a predefined location. The data is then passed to a Google Sheets node named "Append Weather to Sheet", which stores all the key values into a structured spreadsheet. A Set or Function node generates a clean, styled HTML email using inline CSS and the weather values. Finally, a Gmail node sends this report to one or more recipients with a clear subject line and formatted body. How to set up? Create/Open your n8n instance (Cloud or Self-hosted). Connect the following credentials: Google Sheets (OAuth2) Gmail (OAuth2) Set your OpenWeather API key in the HTTP Request node (api.openweathermap.org). Replace latitude/longitude in the request URL as per your location. Link a Google Sheet and define the correct tab name and headers. Configure recipient email(s) in the Gmail node. Deploy the workflow and test. Requirements n8n account (self-hosted or cloud) OpenWeather API key (free or paid) Google account with access to: Google Sheets Gmail A valid Google Sheet created with the following headers (columns): Country Location Latitude Location Longitude Temperature (°C) Feels Like (°C) Min Temp (°C) Max Temp (°C) Humidity (%) Pressure (hPa) Sea Level (hPa) Ground Level (hPa) Visibility (m) Wind Speed (m/s) Wind Direction (°) Wind Gust (m/s) Cloudiness (%) Sunrise (UTC) Sunset (UTC) Date Time (UTC) How to customize? Change the scheduled time in the Schedule Trigger node. Modify the location coordinates in the OpenWeather API URL. Update the HTML template with different formatting or styling. Add a second email or sheet for energy output to correlate with weather. Extend the workflow with Slack, Notion, or Telegram alerts. Add‑ons Integrate with a solar energy API to track power production with weather. Post weather summaries to Notion, Slack or internal dashboards. Generate a visual chart in Google Sheets over time using the collected data. Trigger alerts when specific thresholds are exceeded (e.g., wind gust > 10 m/s). Use Case Examples Solar farm reporting**: Monitor daily weather impact on solar panel output. Logistics planning**: Notify teams of visibility or wind risks before dispatch. Site operations**: Send forecasts to maintenance or ground staff. Academic/weather logging**: Track atmospheric data over time. Common Troubleshooting | Issue | Possible Cause | Solution | | ------------------------------ | ---------------------------------------- | --------------------------------------------------------- | | Email not sent | Gmail credentials not connected properly | Reconnect Gmail account via n8n credential manager | | Weather data is missing fields | API response changed or API key invalid | Verify OpenWeather API key and URL format | | Google Sheet not updating | Incorrect spreadsheet ID or tab name | Double-check spreadsheet ID and sheet name in node | | HTML email renders incorrectly | Broken or missing tags in HTML | Test output HTML separately in browser/email preview tool | Need Help? If you need assistance setting up or customizing this workflow, feel free reach out. We’re here to help!. An n8n automation workflow template by WeblineIndia.

By Oneclick AI Squad

This automated n8n workflow checks daily class schedules, syncs upcoming classes to Google Calendar, and sends reminder notifications to students via email or SMS. Perfect for educational institutions to keep students informed about their daily classes and schedule changes. What This Workflow Does: Automatically checks class schedules every day Identifies today's classes and upcoming sessions Syncs class information to Google Calendar Sends personalized reminders to enrolled students Tracks reminder delivery status and logs activities Handles both email and SMS notification preferences Main Components Daily Schedule Check** - Triggers daily to check class schedules Read Class Schedule** - Retrieves today's class schedule from database/Excel Filter Today's Classes** - Identifies classes happening today Has Classes Today?** - Checks if there are any classes scheduled Read Student Contacts** - Gets student contact information for enrolled classes Sync to Google Calendar** - Creates/updates events in Google Calendar Create Student Reminders** - Generates personalized reminder messages Split Into Batches** - Processes reminders in manageable batches Email or SMS?** - Routes based on student communication preferences Prepare Email Reminders** - Creates email reminder content Prepare SMS Reminders** - Creates SMS reminder content Read Reminder Log** - Checks previous reminder history Update Reminder Log** - Records sent reminders Save Reminder Log** - Saves updated log data Essential Prerequisites Class schedule database/Excel file with student enrollments Student contact database with email and phone numbers Google Calendar API access and credentials SMTP server for email notifications SMS service provider (Twilio, etc.) for text reminders Reminder log file for tracking sent notifications Required Data Files: class_schedule.xlsx: Class ID | Class Name | Date | Time | Duration Instructor | Room | Students Enrolled | Status student_contacts.xlsx: Student ID | Name | Email | Phone | Preferred Contact Program | Class IDs | Active Status reminder_log.xlsx: Log ID | Date | Student ID | Class ID | Contact Method Status | Sent Time | Response Key Features ⏰ Daily Automation:** Runs automatically every day 📅 Calendar Sync:** Syncs classes to Google Calendar 📧 Smart Reminders:** Sends email or SMS based on preference 👥 Batch Processing:** Handles multiple students efficiently 📊 Activity Logging:** Tracks all reminder activities 🔄 Duplicate Prevention:** Avoids sending multiple reminders 📱 Multi-Channel:** Supports both email and SMS notifications Quick Setup Import workflow JSON into n8n Configure daily trigger schedule Set up class schedule and student contact files Connect Google Calendar API credentials Configure SMTP server for emails Set up SMS service provider (Twilio) Test with sample class data Activate workflow Parameters to Configure schedule_file_path: Path to class schedule file contacts_file_path: Path to student contacts file google_calendar_id: Google Calendar ID for syncing google_api_credentials: Google Calendar API credentials smtp_host: Email server settings smtp_user: Email username smtp_password: Email password sms_api_key: SMS service API key sms_phone_number: SMS sender phone number Sample Reminder Messages Email:** "Hi [Name], reminder: [Class Name] starts at [Time] in [Room]. See you there!" SMS:** "[Name], your [Class Name] class starts at [Time] in [Room]. Don't miss it!" Use Cases Daily class reminders for students Schedule change notifications Exam and assignment deadline alerts Teacher absence notifications Room change announcements. An n8n automation workflow template by Oneclick AI Squad.

By Oneclick AI Squad

This automated n8n workflow processes student applications on a scheduled basis, validates data, updates databases, and sends welcome communications to students and guardians. Main Components Trigger at Every Day 7 am** - Scheduled trigger that runs the workflow daily Read Student Data** - Reads pending applications from Excel/database Validate Application Data** - Checks data completeness and format Process Application Data** - Processes validated applications Update Student Database** - Updates records in the student database Prepare Welcome Email** - Creates personalized welcome messages Send Email** - Sends welcome emails to students/guardians Success Response** - Confirms successful processing Error Response** - Handles any processing errors Essential Prerequisites Excel file with student applications (student_applications.xlsx) Database access for student records SMTP server credentials for sending emails File storage access for reading application data Required Excel File Structure (student_applications.xlsx): Application ID | First Name | Last Name | Email | Phone Program Interest | Grade Level | School | Guardian Name | Guardian Phone Application Date | Status | Notes Expected Input Data Format: { "firstName": "John", "lastName": "Doe", "email": "john.doe@example.com", "phone": "+1234567890", "program": "Computer Science", "gradeLevel": "10th Grade", "school": "City High School", "guardianName": "Jane Doe", "guardianPhone": "+1234567891" } Key Features ⏰ Scheduled Processing:** Runs daily at 7 AM automatically 📊 Data Validation:** Ensures application completeness 💾 Database Updates:** Maintains student records 📧 Auto Emails:** Sends welcome messages ❌ Error Handling:** Manages processing failures Quick Setup Import workflow JSON into n8n Configure schedule trigger (default: 7 AM daily) Set Excel file path in "Read Student Data" node Configure database connection in "Update Student Database" node Add SMTP settings in "Send Email" node Test with sample data Activate workflow Parameters to Configure excel_file_path: Path to student applications file database_connection: Student database credentials smtp_host: Email server address smtp_user: Email username smtp_password: Email password admin_email: Administrator notification email. An n8n automation workflow template by Oneclick AI Squad.

By Trung Tran

📚 Telegram RAG Chatbot with PDF Document & Google Drive Backup An upgraded Retrieval-Augmented Generation (RAG) chatbot built in n8n that lets users ask questions via Telegram and receive accurate answers from uploaded PDFs. It embeds documents using OpenAI and backs them up to Google Drive. 👤 Who’s it for Perfect for: Knowledge workers who want instant access to private documents Support teams needing searchable SOPs and guides Educators enabling course material Q&A for students Individuals automating personal document search + cloud backup ⚙️ How it works / What it does 💬 Telegram Chat Handling User sends a message Triggered by the Telegram bot, the workflow checks if the message is text. Text message → OpenAI RAG Agent If the message is text, it's passed to a GPT-powered document agent. This agent: Retrieves relevant info from embedded documents using semantic search Returns a context-aware answer to the user Send answer back The bot sends the generated response back to the Telegram user. Non-text input fallback If the message is not text, the bot replies with a polite unsupported message. 📄 PDF Upload and Embedding User uploads PDFs manually A manual trigger starts the embedding flow. Default Data Loader Reads and chunks the PDF(s) into text segments. Insert to Vector Store (Embedding) Text chunks are embedded using OpenAI and saved for retrieval. Backup to Google Drive The original PDF is uploaded to Google Drive for safekeeping. 🛠️ How to set up Telegram Bot Create via BotFather Connect it to the Telegram Trigger node OpenAI Use your OpenAI API key Connect the Embeddings and Chat Model nodes (GPT-3.5/4) Ensure both embedding and querying use the same Embedding node Google Drive Set up credentials in n8n for your Google account Connect the “Backup to Google Drive” node PDF Ingestion Use the “Upload your PDF here” trigger Connect it to the loader, embedder, and backup flow ✅ Requirements Telegram bot token OpenAI API key (GPT + Embeddings) n8n instance (self-hosted or cloud) Google Drive integration PDF files to upload 🧩 How to customize the workflow | Feature | How to Customize | |-------------------------------|-------------------------------------------------------------------| | Auto-ingest from folders | Add Google Drive/Dropbox watchers for new PDFs | | Add file upload via Telegram | Extend Telegram bot to receive PDFs and run the embedding flow | | Track user questions | Log Telegram usernames and questions to a database | | Summarize documents | Add summarization step on upload | | Add Markdown or HTML support | Format replies for better Telegram rendering | Built with 💬 Telegram + 📄 PDF + 🧠 OpenAI Embeddings + ☁️ Google Drive + ⚡ n8n. An n8n automation workflow template by Trung Tran.

By Janak Patel

Who’s it for This template is ideal for YouTube video creators who spend a lot of time manually generating SEO assets like descriptions, tags, titles, keywords, and thumbnails. If you're looking to automate your YouTube SEO workflow, this is the perfect solution for you. How it works / What it does Connect a Google Sheet to n8n and pull in the Hindi script (or any language). Use OpenAI to generate SEO content: Video description Tags Keywords Titles Thumbnail titles etc. Use the generated description as input to create a thumbnail image using an image generation API. Store all outputs in the same Google Sheet in separate columns. Optionally, use tools like VidIQ or TubeBuddy to test the SEO strength of generated titles, tags, and keywords. 💡 Note: This example uses Runway’s image generation API, but you can plug in any other image-generation service of your choice. Requirements A Google Sheet with clearly named columns Hindi, English, or other language scripts in the sheet OpenAI API key Runway API key (or any other image generation API) How to set up You can set up this workflow in 15 minutes by following the pre-defined steps. Replace the manual Google Sheet trigger with a scheduled trigger for daily or timed automation. You may also swap Google Sheets with any database or data source of your choice. No Google Sheets API required. Requires minimal JavaScript or Python knowledge for advanced customizations. An n8n automation workflow template by Janak Patel.

By Rahul Joshi

Description: This ready-to-deploy n8n automation template smartly detects and classifies files uploaded to a specified Google Drive folder based on MIME type. It automatically moves each file into its correct destination folder: Documents, PDFs, or Images — ensuring a clean and organized Drive, effortlessly. Perfect for remote teams, admins, educators, legal pros, and automation-focused operations, this workflow eliminates manual sorting and saves hours of repetitive work. What This Template Does (Step-by-Step) ⚙️Manual Trigger: Launch the workflow on demand using the "Execute Workflow" trigger. 📁 Search Files in Source Folder (Google Drive): Lists all files inside your chosen folder (e.g., "Uploads"). 🔁 Loop Over Files (SplitInBatches): Iterates through each file one-by-one to ensure reliability. 📥 Download File (Google Drive): Retrieves file metadata and MIME type required for filtering. 🧠 Smart File Type Detection via If Nodes application/json → Move to Documents folder application/pdf → Move to PDFs folder image/jpeg → Move to Images folder (Easily customizable to support additional types like PNG, DOCX, etc.) 📂 Move Files to Designated Folders: Uses Google Drive API to relocate each file to its proper location. 🔁 Loop Returns for Next File After each move, the loop picks the next file in queue. Key Features ⚙️ Google Drive API v3 Integration 🔐 OAuth2 for secure access 📄 MIME-type–based routing logic 🔁 Batch-safe with looping logic ✅ File properties are preserved 🔄 Auto-removal from source after sorting Required Integration Google Drive (OAuth2) Use Cases Auto-organize client uploads Separate scanned PDFs, images, or forms Route invoices, receipts, or contracts into folders Automatically sort uploaded assignments or resources Maintain structured cloud storage without manual intervention Why Use This Template? ✅ No-code deployment ✅ Saves hours of manual work ✅ Works across teams, departments, or shared Drives ✅ Easy to expand with more file types or routing rules ✅ Keeps your Drive clean, fast, and organized. An n8n automation workflow template by Rahul Joshi.

By Thiago Vazzoler Loureiro

Description Automates the forwarding of messages from WhatsApp (via Evolution API) to Chatwoot, enabling seamless integration between external WhatsApp users and internal Chatwoot agents. It supports both text and media messages, ensuring that customer conversations are centralized and accessible for support teams. What Problem Does This Solve? Managing conversations across multiple platforms can lead to fragmented support and lost context. This subworkflow bridges the gap between WhatsApp and Chatwoot, automatically forwarding messages received via the Evolution API to a Chatwoot inbox. It simplifies communication flow, centralizes conversations, and enhances the support team's productivity. Features Support for plain text messages Support for media messages: images, videos, documents, and audio Automatic media upload to Chatwoot with proper attachment rendering Automatic contact association using WhatsApp number and Chatwoot API Designed to work with Evolution API webhooks or any message source Prerequisites Before using this automate, make sure you have: Evolution API credentials with incoming message webhook configured A Chatwoot instance with access token and API endpoint An existing Chatwoot inbox (preferably API channel) A configured HTTP Request node in n8n for Chatwoot API calls Suggested Usage This subworkflow should be attached to a parent workflow that receives WhatsApp messages via the Evolution API webhook. Ideal for: Centralized customer service operations WhatsApp-to-CRM/chat routing Hybrid automation workflows where human agents need to reply from Chatwoot It ensures that all incoming WhatsApp messages are properly converted and forwarded to Chatwoot, preserving message content and structure. An n8n automation workflow template by Thiago Vazzoler Loureiro.

By Naveen Choudhary

This workflow automatically enriches company domain lists with comprehensive business information using Perplexity AI's research capabilities and organizes the data in Google Sheets for easy analysis and use. Who's it for Sales teams** building prospect databases with accurate contact information Marketing professionals** researching target companies for campaigns Business development teams** gathering competitive intelligence Data analysts** enriching existing company datasets Researchers** collecting business information for market analysis How it works The workflow reads unprocessed company domains from a Google Sheets document, processes them in batches of 10 using Perplexity AI to research detailed business information, then saves the enriched data back to the spreadsheet. It focuses on German addresses but can be customized for any region. What it does Fetches unprocessed domains - Reads company domains from Google Sheets that haven't been processed yet Batches for efficiency - Groups domains into batches of 10 to optimize API costs and performance AI-powered research - Uses Perplexity AI to find comprehensive business data for each company Parses structured data - Converts AI responses into clean, structured JSON format Updates spreadsheet - Saves enriched data and marks domains as processed to prevent duplicates Requirements Perplexity AI API key** (Get one here) Google Sheets API access** (OAuth2 credentials) Google Sheets template** - Make a copy of this template How to set up Make a copy of the template Google Sheet and update the document ID in both Google Sheets nodes Configure Perplexity AI credentials in the HTTP Request node Set up Google Sheets OAuth2 authentication Add your company domains to the "domain" column in the Data tab Leave the "processed" column empty for new domains Run the workflow using the manual trigger How to customize the workflow Change target region**: Modify the AI prompt to research addresses in different countries Adjust batch size**: Change the batch size in the "Batch Process Domains" node (smaller batches = lower costs) Add custom fields**: Extend the AI prompt and Google Sheets mapping to include additional data points Automate execution**: Replace Manual Trigger with Schedule Trigger for regular processing Filter criteria**: Modify the Google Sheets filter to process specific subsets of domains Output data includes Complete company address (street, city, state, postal code, country) International phone number format Latest employee count and annual revenue (USD) Industry classification LinkedIn company URL Reliable source URL for verification Processing status tracking. An n8n automation workflow template by Naveen Choudhary.

By Robert Breen

This n8n workflow automatically generates a custom YouTube thumbnail using OpenAI’s DALL·E based on a YouTube video’s transcript and title. It uses Apify actors to extract video metadata and transcript, then processes the data into a prompt for DALL·E and creates a high-resolution image for use as a thumbnail. ✅ Key Features 📥 Form Trigger**: Accepts a YouTube URL from the user. 🧠 GPT-4o Prompt Creation**: Summarizes transcript and title into a descriptive DALL·E prompt. 🎨 DALL·E Image Generation**: Produces a clean, minimalist YouTube thumbnail with OpenAI’s image model. 🪄 Automatic Image Resizing**: Resizes final image to YouTube specs (1280x720). 🔍 Apify Integration**: Uses two Apify actors: Youtube-Transcript-Scraper to extract transcript youtube-scraper to get video metadata like title, channel, etc. 🧰 What You'll Need OpenAI API Key** Apify Account & API Token** YouTube video URL** n8n instance (cloud or self-hosted)** 🔧 Step-by-Step Setup 1️⃣ Form & Parameter Assignment Node**: Form Trigger How it works**: Collects the YouTube URL via a form embedded in your n8n instance. API Required**: None Additional Node**: Set Converts the single input URL into the format Apify expects: an array of { url } objects. 2️⃣ Apify Actors for Data Extraction Node**: HTTP Request (Query Metadata) URL: https://api.apify.com/v2/acts/streamers~youtube-scraper/run-sync-get-dataset-items Payload: JSON with startUrls array and filtering options like maxResults, isHD, etc. Node**: HTTP Request (Query Transcript) URL: https://api.apify.com/v2/acts/topaz_sharingan~Youtube-Transcript-Scraper/run-sync-get-dataset-items Payload: startUrls array API Required**: Apify API Token (via HTTP Query Auth) Notes**: You must have an Apify account and actor credits to use these actors. 3️⃣ OpenAI GPT-4o & DALL·E Generation Node**: OpenAI (Prompt Creator) Uses the transcript and title to generate a DALL·E-compatible visual prompt. Node**: OpenAI (Image Generator) Resource: image Model: DALL·E (default with GPT-4o key) API Required**: OpenAI API Key Prompt Strategy**: Create a minimalist YouTube thumbnail in an illustration style. The background should be a very simple, uncluttered setting with soft, ambient lighting that subtly reflects the essence of the transcript. The overall mood should be professional and non-cluttered, ensuring that the text overlay stands out without distraction. Do not include any text. 4️⃣ Resize for YouTube Format Node**: Edit Image Purpose**: Resize final image to 1280x720 with ignoreAspectRatio set to true. No API required** — this runs entirely in n8n. 👤 Created By Robert Breen Automation Consultant | AI Workflow Designer | n8n Expert 📧 robert@ynteractive.com 🌐 ynteractive.com 🔗 LinkedIn 🏷️ Tags openai dalle youtube thumbnail generator apify ai automation image generation illustration prompt engineering gpt-4o. An n8n automation workflow template by Robert Breen.

By Kanaka Kishore Kandregula

This workflow analyses completed orders from the past 3 months to identify high-value customers, generates unique voucher codes for each, and sends them a professionally designed promotional email. This n8n template helps Magento 2 merchants automatically send customised, beautifully branded coupon emails to high-value customers. The workflow connects to Magento 2’s REST API to retrieve your store logo and secure base URL. It either generates a coupon code and then crafts a visually appealing HTML email with dynamic customer details and branding. You can integrate this flow as part of loyalty campaigns or customer milestone automations. All styling is mobile-responsive and minimal to reduce the chance of spam filtering while still delivering a modern user experience. 🔍 What It Does: Authenticates and connects to your Magento 2 store. Fetches store logo and base media URL using API calls. Processes High valued customers. Generates coupons for each customers Dynamically injects customer name and unique coupon code. Sends a fully branded and styled HTML email. ⚙️ Technical Highlights: Uses rest/all/V1/store/storeConfigs to retrieve logo and configuration data. HTML email styled with CSS media queries for prefers-color-scheme. Gradient background with fallbacks and proper semantic structure. Works with Gmail, Apple Mail, Outlook (Mac), and others. Uses n8n expressions to handle personalization logic without external scripts. ✅ Ideal For: Magento 2 store owners. Digital marketers targeting loyal or VIP customers. CRM/email marketing automation professionals. Agencies building Magento-based growth funnels. 📈 Why This Matters in the Current Market: Modern customers expect personalized, premium communication — and inbox competition is tougher than ever. This workflow enables eCommerce merchants to deliver clean, brand-consistent emails using automation — all without plugins or frontend code changes. 🔧 Modules Used: HTTP Request – Fetch Magento logo and config via REST API. Set – Store customer name and coupon values. Email or SMTP – Sends the composed HTML email. DateTime – To handle expiration display (optional). HTML Template – Responsive MJML-like styling with fallback-safe design. 💼 Use Cases: Loyalty program campaigns Seasonal or holiday discount blasts Surprise reward drops for top spenders Post-purchase thank-you automation Reactivation flows for high-valuee users 🔒 Credentials Required: Magento 2 Admin API Token (Optional) SMTP credentials or Email node configuration 📂 Category E-commerce → Magento 2 (Adobe Commerce) 💬 Need Help? 💡 Having trouble setting it up or want to customize this workflow further? Feel free to reach out — I’m happy to help with setup, customization, or Magento 2 API integration issues. Contact: Author 👤 Author Kanaka Kishore Kandregula Certified Magento 2 Developer https://gravatar.com/kmyprojects https://www.linkedin.com/in/kanakakishore. An n8n automation workflow template by Kanaka Kishore Kandregula.

By Grant Warfield

This workflow auto-generates and posts a tweet once per day using real-time insights from the web. It uses Perplexity to fetch trending topics, OpenAI to summarize them into a tweet, and the Twitter API to publish. ⚙️ Set up steps Set your Perplexity API key in the HTTP Request node. Add your OpenAI API key to the Message Model node. Authenticate your Twitter API credentials in the second HTTP Request node. Modify the schedule trigger to run daily at your preferred time. All logic is pre-configured — simply plug in your credentials and you're live. An n8n automation workflow template by Grant Warfield.

By Arjan ter Heegde

n8n Placeholdarr for Plex (BETA) This flow creates dummy files for every item added in your *Arrs (Radarr/Sonarr) with the tag unprocessed-dummy. It’s useful for maintaining a large Plex library without needing the actual movies or shows to be present on your Debrid provider. How It Works When a dummy file is played, the corresponding item is automatically monitored in *Arr and added to the download queue. This ensures that the content becomes available within ~3 minutes for playback. If the content finishes downloading while the dummy is still being played, Tautulli triggers a webhook that stops the stream and notifies the user. Requirements Each n8n node must have the correct URL and authorization headers configured. The SSH host (used to create dummy files) must have FFmpeg installed. A Trakt.TV API key is required if you're using Trakt collections. Warning > ⚠️ This flow is currently in BETA and under active development. > It is not recommended for users without technical experience. > Keep an eye on the GitHub repository for updates. https://github.com/arjanterheegde/n8n-workflows-for-plex. An n8n automation workflow template by Arjan ter Heegde.

By Nabin Bhandari

This n8n template automatically creates and publishes high-quality LinkedIn posts using your brand brief, AI-generated ideas, and structured feedback loops — all powered by OpenAI. Perfect for solo creators, marketers, and startup teams building a consistent presence on LinkedIn. Who's it for Creators and freelancers building a personal brand Social media managers at startups or agencies Marketing teams that want to scale LinkedIn content Anyone tired of manually ideating, writing, and posting daily What it does Triggers daily at a chosen time (default: 9 PM) Fetches new content ideas from your idea-generation workflow Loads your brand brief and previous post feedback Uses OpenAI to craft a branded, engaging LinkedIn post Publishes directly to LinkedIn — no manual copy-paste needed How the AI logic works The AI agent follows a consistent, looped prompt strategy to ensure brand alignment: ++Prompt++ You are a helpful content creator for Nabin Bhandari's personal brand. Use the below steps to create content: Always start by getting the brand brief using the Get_Brand_Brief tool. Create a post on the requested topic that aligns with the brand brief. Get feedback and a score on the post using the Get_Content_Feedback tool. If the score is below 0.8, use the feedback to refine the post and repeat. The final output should be the approved post. Bonus: You can fine-tune OpenAI on your own brand tone and style by uploading at least 50 examples of approved posts. This will help ensure even more accurate, on-brand outputs. Requirements OpenAI API Key LinkedIn API credentials set in the LinkedIn node A Notion page (or any storage) with your Brand Brief clearly described Optional: Fine-tuned OpenAI model for higher fidelity How to customize Adjust the AI prompt for different tones (e.g., witty, professional) Swap the idea source (Airtable, Notion, Webhook, etc.) Add manual approval steps before publishing Replace the LinkedIn node with other social media APIs (Twitter/X, Threads) Tips Store a clear and specific brand brief in your Notion page — it directly shapes the AI's tone Add a database of previously approved posts for fine-tuning OpenAI Use additional feedback metrics (likes, engagement) for future iterations. An n8n automation workflow template by Nabin Bhandari.

By mariskarthick

🚨Are alert storms overwhelming your Security Operations workflows? This n8n workflow supercharges your SOC by fully automating triage, analysis, and notification for Wazuh alerts—blending event-driven automation, OpenAI-powered contextual analysis, and real-time collaboration for incident response. 🔑 Key Features: ✅ Automated Triage: Instantly filters Wazuh alerts by severity to focus analyst effort on the signals that matter. 🤖 AI-Driven Investigation Reports: Uses OpenAI's GPT-4o-mini to auto-generate context-rich incident reports, including: MITRE Tactic & Technique mapping Impacted scope (IP addresses, hostnames) External artifact reputation checks Actionable security recommendations Fully customizable prompt format aligned with your SOC playbooks 📡 Multi-Channel Notification Delivers clean, actionable reports directly to your SOC team via Telegram. Easily extendable to Slack, Outlook, Gmail, Discord, or any other preferred channel. 🔇 Noise Reduction Eliminates alert fatigue using smart filters and custom AI prompts that suppress false positives and highlight real threats. 🔧 Fully Customizable Tweak severity thresholds, update prompt logic, or integrate additional data sources and channels — all with minimal effort ⚙️ How It Works Webhook Listens for incoming Wazuh alerts in real time. If Condition Filters based on severity (1 low, 2 medium, etc.) or other logic you define. AI Investigation (LangChain + OpenAI) Summarizes full alert logs and context using custom prompts to generate: Incident Overview Key Indicators Log Analysis Threat Classification Risk Assessment Security Recommendations Notification Delivery The report is parsed, cleaned, and sent to your SOC team in real-time, enabling rapid response — even during high-alert volumes. No-Op Path Efficiently discards irrelevant alerts without breaking the flow. 🧠 Why n8n + AI? Traditional alert triage is manual, slow, and error-prone — leading to analyst burnout and missed critical threats. This workflow shows how combining workflow automation with a tailored AI model enables your SOC to shift from reactive to proactive. Analysts can now: Focus on critical investigations Respond to alerts faster Eliminate copy-paste fatigue Get instant contextual summaries > ⚠️ Note: We learned that generic AI isn’t enough. Context-rich prompts and alignment with your actual SOC processes are key to meaningful, scalable automation. 🚀 Ready to build a smarter, less stressful SOC? Clone this workflow, adapt it to your processes, and never miss a critical alert again. 📬 Contributions welcome! Feel free to raise PRs, suggest new enhancements, or fork for your own use cases. Created by Mariskarthick M Senior Security Analyst | Detection Engineer | Threat Hunter | Open-Source Enthusiast. An n8n automation workflow template by mariskarthick.

By keisha kalra

Try It Out! This n8n template creates a fully automated Instagram content schedule using AI and Google Sheets. It is perfect for content creators, marketing teams, or local businesses looking to organize and scale their social media posting. How it works The workflow starts by reading two sets of inputs from a Google Sheet: Your content strategy inputs (Pillar, Objective, Frequency, Format, Structure, Examples). A list of scraped blog posts with title, URL, and description (fetched from your website). Blog posts are scraped using Apify and parsed to extract key fields, which are stored in a tab labeled "Input (blog month)". You can assign a preferred posting month for each blog (e.g. fall blog posts get tagged for September). The workflow then merges both inputs and extracts the relevant information for further information added by ChatGPT. AI Scheduling & Personalization Once merged, the workflow loops through each content item and: Identifies if the scheduled post falls on or near a holiday (like Mother’s Day) and adjusts the content accordingly. A reference tool is attached to guide structure and tone, based on a library of post examples. Sends the content to an AI Agent (using GPT-4, but customizable) that generates: A compelling Instagram caption A visual description Hashtags Suggested post date, day, content pillar, and format (carousel, reel, image, etc.) Output All generated content including captions, structure, dates, hashtags, and pillar is exported into a tab titled Output in your Google Sheet. The final schedule is ready for manual review, editing, or publishing to social media. How to use The workflow uses a manual trigger to start, but you can replace it with a Webhook, cron job, or form submission. Add/edit your content strategy in Google Sheets. How to Set-Up Initial Input Tab Define your content pillars and structure Create a tab named "Input" or "Strategy" Include these columns: Pillar: e.g., Family images Objective: e.g., Showcase images Frequency: e.g., Bi-weekly Content Form: e.g., Images, Reels Structure: brief description of expected layout (e.g., carousel Q&A, singular photo) Examples: prompts or questions to guide AI (e.g., Why do you think families should do a session?) Input (blog month) Tab – Store scraped blog content Include these columns: URL: direct link to blog post Title: blog post title Description: short summary of the post Preferred Month: month you want it posted (e.g., August, September) This sheet is partially auto-filled by the workflow (except for Preferred Month) Output Tab – Final scheduled content Include these columns: Date: scheduled posting date (YYYY-MM-DD) Day: day of the week Pillar: content category assigned Format: e.g., Images, Reels, Carousel Description: visual summary Caption: Instagram-ready caption Hashtags: complete hashtag block To use the Apify HTTP Request node: Drag in an HTTP Request node into your n8n workflow. Set the Method and URL based on how you're using Apify: Use POST if you want to run an actor live with dynamic input (e.g. scrape blog posts in real time). Use GET if you want to retrieve results from a completed or static dataset run (faster and cheaper if you're reusing previous data). Configure query or body parameters: Include your Apify API token for authentication (e.g. token=YOUR_API_KEY) For POST: include an input object with any required actor settings (e.g., blog URL to scrape). For GET: specify the dataset ID in the URL Test the node to ensure you're retrieving the blog titles, descriptions, and URLs as expected. Requirements Apify account for scraping blog posts OpenAI key (e.g. GPT-4) or another model of your choice Google Sheets Credentials Example Use Cases A photographer repurposing blogs into Instagram carousels A nonprofit automatically generating seasonal posts A small team managing multi-pillar content across weeks or months Need Help? Join the n8n Discord or ask in the n8n Forum! Happy Content Making ! 📅✨. An n8n automation workflow template by keisha kalra.

By Automate With Marc

🎥 Telegram Image-to-Video Generator Agent (Veo3 / Seedance Integration) ⚠️ This template uses [community nodes] and some credential-based HTTP API calls (e.g. Seedance/Wavespeed). Ensure proper credentials are configured before running. 🛠️ In the accompanying video tutorial, this logic is built as two separate workflows: Telegram → Image Upload + Prompt Agent Prompt Output → Video Generation via API Watch Full Video Tutorial: https://youtu.be/iaZHef5bZAc&list=PL05w1TE8X3baEGOktlXtRxsztOjeOb8Vg&index=1 ✨ What This Workflow Does This powerful automation allows you to generate short-form videos from a Telegram image input and user prompt — perfect for repurposing content into engaging reels. From the moment a user sends a photo with a caption to your Telegram bot, this n8n workflow: 📸 Captures the image and saves it to Google Drive 🧠 Uses an AI Agent (via LangChain + OpenAI) to craft a Seedance/Veo3-compatible video prompt 📑 Logs the interaction to a Google Sheet 🎞️ Sends the prompt + image to the Seedance (Wavespeed) API to generate a video 🚀 Sends the resulting video back to the user on Telegram — fully automated 🔗 How It Works (Step-by-Step) Telegram Bot Trigger Listens for incoming images and captions Conditional Logic Filters out invalid inputs AI Agent (LangChain) Uses OpenAI GPT to: Generate a video prompt Attach the most recent image URL (from Google Sheet) Google Drive Upload Saves the Telegram image and logs the share link Google Sheets Logging Appends a new row with date + file link Wavespeed (Seedance/Veo3) API Calls the /bytedance/seedance-v1-pro-i2v-480p endpoint with image and prompt Video Polling & Output Waits for generation completion Sends back final video file to Telegram user 🛠️ Tools & APIs Used Telegram Bot (Trigger + Video Reply) LangChain Agent Node OpenAI GPT-4.1-mini for Prompt Generation Simple Memory & Tools (Google Sheets) Google Drive (Image upload) Google Sheets (Log prompts + image URLs) Wavespeed / Seedance API (Image-to-video generation) 🧩 Requirements Before running this workflow: ✅ Set up a Telegram Bot and configure credentials ✅ Connect your Google Drive and Google Sheets credentials ✅ Sign up for Wavespeed / Seedance and generate an API key ✅ Replace placeholder values in: HTTP Request nodes Google Drive folder ID Google Sheet document ID 📦 Suggested Use Cases Generate short-form videos from image ideas Reformat static images into dynamic reels Repurpose visual content for TikTok/Instagram. An n8n automation workflow template by Automate With Marc.

By vinci-king-01

How it works Transform your business with intelligent deal monitoring and automated customer engagement! This AI-powered coupon aggregator continuously tracks competitor deals and creates personalized marketing campaigns that convert. Key Steps 24/7 Deal Monitoring - Automatically scans competitor websites daily for the best deals and offers Smart Customer Segmentation - Uses AI to intelligently categorize and target your customer base Personalized Offer Generation - Creates tailored coupon campaigns based on customer behavior and preferences Automated Email Marketing - Sends targeted email campaigns with personalized deals to the right customers Performance Analytics - Tracks campaign performance and provides detailed insights and reports Daily Management Reports - Delivers comprehensive analytics to management team every morning Set up steps Setup time: 10-15 minutes Configure competitor monitoring - Add target websites and deal sources you want to track Set up customer database - Connect your customer data source for intelligent segmentation Configure email integration - Connect your email service provider for automated campaigns Customize deal criteria - Define what types of deals and offers to prioritize Set up analytics tracking - Configure Google Sheets or database for performance monitoring Test automation flow - Run a test cycle to ensure all integrations work smoothly Never miss a profitable deal opportunity - let AI handle the monitoring and targeting while you focus on growth!. An n8n automation workflow template by vinci-king-01.

By vinci-king-01

How it works Turn Amazon into your personal competitive intelligence goldmine! This AI-powered workflow automatically monitors Amazon markets 24/7, delivering deep competitor insights and pricing intelligence that would take you 10+ hours of manual research weekly. Key Steps Daily Market Scan - Runs automatically at 6:00 AM UTC to capture fresh competitive data AI-Powered Analysis - Uses ScrapeGraphAI to intelligently extract pricing, product details, and market positioning Competitive Intelligence - Analyzes competitor strategies, pricing gaps, and market opportunities Keyword Goldmine - Identifies high-value keyword opportunities your competitors are missing Strategic Insights - Generates actionable recommendations for pricing and positioning Automated Reporting - Delivers comprehensive market reports directly to Google Docs Set up steps Setup time: 15-20 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key for intelligent web scraping Set up Google Docs integration - Connect Google OAuth2 for automated report generation Customize Amazon search URL - Target your specific product category or market niche Configure IP rotation - Set up proxy rotation if needed for large-scale monitoring Test with sample products - Start with a small product set to validate data accuracy Set competitive alerts - Define thresholds for price changes and market opportunities Save 10+ hours weekly while staying ahead of your competition with real-time market intelligence!. An n8n automation workflow template by vinci-king-01.

By Anna Bui

This n8n template automatically syncs website visitors identified by RB2B into your Attio CRM, creating comprehensive contact records and associated sales deals for immediate follow-up. Perfect for sales teams who want to capture every website visitor as a potential lead without manual data entry! Good to know RB2B identifies anonymous website visitors and sends structured data via Slack notifications The workflow prevents duplicate contacts by checking email addresses before creating new records All RB2B leads are automatically tagged with source tracking for easy identification How it works RB2B sends website visitor notifications to your designated Slack channel with visitor details The workflow extracts structured data from Slack messages including name, email, company, LinkedIn, and location It searches Attio CRM to check if the person already exists based on email address For new visitors, it creates a complete contact record with all available information For existing contacts, it updates their record and manages deal creation intelligently Automatically creates sales deals tagged as "RB2B Website Visitor" for proper lead tracking How to use Configure RB2B to send visitor notifications to a dedicated Slack channel The Slack trigger can be replaced with other triggers like webhooks if you prefer different notification methods Customize the deal naming conventions and stages to match your sales pipeline Requirements RB2B account with Slack integration enabled Attio CRM account with API access Slack workspace with bot permissions for the designated RB2B channel Customising this workflow Modify deal stages and values based on your sales process Add lead scoring based on company domain or visitor behavior patterns Integrate additional enrichment APIs to enhance contact data Set up automated email sequences or Slack notifications for high-value leads. An n8n automation workflow template by Anna Bui.

By Peter Zendzian

This n8n template demonstrates how to build an intelligent entity research system that automatically discovers, researches, and creates comprehensive profiles for business entities, concepts, and terms. Use cases are many: Try automating glossary creation for technical documentation, building standardized definition databases for compliance teams, researching industry terminology for content creation, or developing training materials with consistent entity explanations! Good to know Each entity research typically costs $0.08-$0.34, depending on the complexity and sources required. The workflow includes smart duplicate detection to minimize unnecessary API calls. The workflow requires multiple AI services and a vector database, so setup time may be longer than simpler templates. Entity definitions are stored locally in your Qdrant database and can be reused across multiple projects. How it works The workflow checks your existing knowledge base first to avoid duplicate research on entities you've already processed. If the entity is new, an AI research agent intelligently combines your vector database, Wikipedia, and live web research to gather comprehensive information. The system creates structured entity profiles with definitions, categories, examples, common misconceptions, and related entities - perfect for business documentation. AI-powered validation ensures all entity profiles are complete, accurate, and suitable for business use before storage. Each researched entity gets stored in your Qdrant vector database, creating a growing knowledge base that improves research efficiency over time. The workflow includes multiple stages of duplicate prevention to avoid unnecessary processing and API costs. How to use The manual trigger node is used as an example, but feel free to replace this with other triggers such as form submissions, content management systems, or automated content pipelines. You can research multiple related entities in sequence, and the system will automatically identify connections and relationships between them. Provide topic and audience context to get tailored explanations suitable for your specific business needs. Requirements OpenAI API account for o4-mini (entity research and validation) Qdrant vector database instance (local or cloud) Ollama with nomic-embed-text model for embeddings Automate Web Research with GPT-4, Claude & Apify for Content Analysis and Insights workflow (for live web research capabilities) Anthropic API account for Claude Sonnet 4 (used by the web research workflow) Apify account for web scraping (used by the web research workflow) Customizing this workflow Entity research automation can be adapted for many specialized domains. Try focusing on specific industries like legal terminology (targeting official legal sources), medical concepts (emphasizing clinical accuracy), or financial terms (prioritizing regulatory definitions). You can also customize the validation criteria to match your organization's specific quality standards. An n8n automation workflow template by Peter Zendzian.

By Marth - Business Automation

How It Works: The AI Recruiter Engine This workflow is a powerful, two-phase system designed to automate the entire passive candidate sourcing and engagement cycle. Phase 1: Sourcing & Enrichment This phase is triggered manually and focuses on finding, analyzing, and scoring potential candidates. Manual Trigger: You start the workflow manually by providing a jobTitle and keywords. Code (Generate Search Query): This node uses your input to create a sophisticated search query for an external sourcing platform. HTTP Request (Hunter.io/Clearbit): The workflow queries a third-party API to find public email addresses for the target companies or candidates. Code (Filter Candidates): This node filters the raw data, keeping only candidates who match your basic criteria. Airtable/Google Sheets (Log Candidates): All potential candidates are logged into your centralized database to serve as your simple ATS. Code (AI Analysis & Score): This node prepares a prompt with the candidate's profile data and sends it to a generative AI model (via an HTTP Request). It then calculates a final score based on the AI's analysis and other criteria. If (Is Score > 75?): This node checks if the candidate’s score meets your threshold. If so, they are passed to the next phase; otherwise, they are filtered out. Phase 2: Automated Outreach & Nurturing This phase handles the multi-step, personalized email communication with high-scoring candidates. Gmail (Send Initial Email): The workflow sends a personalized first email using dynamic data from the candidate's profile. Airtable/Google Sheets (Update Status): The candidate's status is updated to Contacted in your database. Wait: The workflow pauses for a set period (e.g., 3 days) to allow time for a response. If (No Reply?): This node checks the candidate's status in your database. If they haven't replied, the workflow proceeds to the next email. Gmail (Send Follow-up): A follow-up email is sent to the candidate. This sequence repeats with a final nurture email to close the loop. How to Set Up Prepare Your Credentials & Database: Database: Create a database in Airtable or Google Sheets with columns for Name, Email, Score, Status, and any other data you want to track. Email: Set up a Gmail or other email service credential in n8n. Sourcing API: Obtain an API key for a sourcing service like Hunter.io to find public email addresses. Import the Workflow: Import the JSON code for the AI Recruiter Engine into your n8n instance. Configure the Nodes: Manual Trigger: When running the workflow, manually input the jobTitle and keywords you are sourcing for. HTTP Request: Update the URL with your sourcing API key. Code Nodes: Review and adjust the JavaScript in the Code nodes to match your specific job criteria and data structure. Airtable/Google Sheets: Connect to your database, select the correct table, and ensure the column names in the node settings match your database. Gmail: Select your email credential and customize the content of the outreach emails in each Gmail node. If: Adjust the finalScore threshold in the If node to your desired value. Test and Activate: Run the workflow once manually to ensure all nodes are configured correctly and data flows as expected. Once you are confident, the workflow is ready to be run for your sourcing campaigns. An n8n automation workflow template by Marth - Business Automation.

By Yaron Been

Generate Custom Text Content with IBM Granite 3.3 8B Instruct AI This workflow connects to Replicate’s API and uses the ibm-granite/granite-3.3-8b-instruct model to generate text. ✅ 🔵 SECTION 1: Trigger & Setup ⚙️ Nodes 1️⃣ On clicking 'execute' What it does:* Starts the workflow manually when you hit *Execute. Why it’s useful:** Perfect for testing text generation on-demand. 2️⃣ Set API Key What it does:* Stores your *Replicate API key** securely. Why it’s useful:** You don’t hardcode credentials into HTTP nodes — just set them once here. Beginner tip:** Replace YOUR_REPLICATE_API_KEY with your actual API key. 💡 Beginner Benefit ✅ No coding needed to handle authentication. ✅ You can reuse the same setup for other Replicate models. ✅ 🤖 SECTION 2: Model Request & Polling ⚙️ Nodes 3️⃣ Create Prediction (HTTP Request) What it does:* Sends a *POST request** to Replicate’s API to start a text generation job. Parameters include:** temperature, max_tokens, top_k, top_p. Why it’s useful:** Controls how creative or focused the AI text output will be. 4️⃣ Extract Prediction ID (Code) What it does:* Pulls the *prediction ID** and builds a URL for checking status. Why it’s useful:** Replicate jobs run asynchronously, so you need the ID to track progress. 5️⃣ Wait What it does:* Pauses for *2 seconds** before checking the prediction again. Why it’s useful:** Prevents spamming the API with too many requests. 6️⃣ Check Prediction Status (HTTP Request) What it does:* Polls the Replicate API for the *current status** (e.g., starting, processing, succeeded). Why it’s useful:** Lets you loop until the AI finishes generating text. 7️⃣ Check If Complete (IF Condition) What it does:* If the status is *succeeded, it goes to “Process Result.” Otherwise, it loops back to **Wait and retries. Why it’s useful:** Creates an automated polling loop without writing complex code. 💡 Beginner Benefit ✅ No need to manually refresh or check job status. ✅ Workflow keeps retrying until text is ready. ✅ Smart looping built-in with Wait + If Condition. ✅ 🟢 SECTION 3: Process & Output ⚙️ Nodes 8️⃣ Process Result (Code) What it does:* Collects the final *AI output**, status, metrics, and timestamps. Adds info like:** ✅ output → Generated text ✅ model → ibm-granite/granite-3.3-8b-instruct ✅ metrics → Performance data Why it’s useful:** Gives you a neat, structured JSON result that’s easy to send to Sheets, Notion, or any app. 💡 Beginner Benefit ✅ Ready-to-use text output. ✅ Easy integration with any database or CRM. ✅ Transparent metrics (when it started, when it finished, etc.). ✅✅✅ ✨ FULL FLOW OVERVIEW | Section | What happens | | ------------------------------ | ---------------------------------------------------------------------------- | | ⚡ Trigger & Setup | Start workflow + set Replicate API key. | | 🤖 Model Request & Polling | Send request → get Prediction ID → loop until job completes. | | 🟢 Process & Output | Extract clean AI-generated text + metadata for storage or further workflows. | 📌 How You Benefit Overall ✅ No coding needed — just configure your API key. ✅ Reliable polling — the workflow waits until results are ready. ✅ Flexible — you can extend output to Google Sheets, Slack, Notion, or email. ✅ Beginner-friendly — clean separation of input, process, and output. ✨ With this workflow, you’ve turned Replicate’s IBM Granite LLM into a no-code text generator — running entirely inside n8n! ✨. An n8n automation workflow template by Yaron Been.

By Oneclick AI Squad

This n8n workflow helps users easily discover nearby residential construction projects by automatically scraping and analyzing property listings from 99acres and other real estate platforms. Users can send an email with their location preferences and receive a curated list of available properties with detailed information, including pricing, area, possession dates, and construction status. Good to know The workflow focuses specifically on residential construction projects and active developments Property data is scraped in real-time to ensure the most current information Results are automatically formatted and structured for easy reading The system handles multiple property formats and data variations from different sources Fallback mechanisms ensure reliable data extraction even when website structures change How it works Trigger: New Email** - Detects incoming emails with property search requests and extracts location preferences from email content Extract Area & City** - Parses the email body to identify target areas (e.g., Gota, Ahmedabad) and falls back to city-level search if specific area is not mentioned Scrape Construction Projects** - Performs web scraping on 99acres and other property websites based on the extracted area and city information Parse Project Listings** - Cleans and formats the scraped HTML data into structured project entries with standardized fields Format Project Details** - Transforms all parsed projects into a consistent email-ready list format with bullet points and organized information Send Results to User** - Delivers a professionally formatted email with the complete list of matching construction projects to the original requester Email Format Examples Input Email Format To: properties@yourcompany.com Subject: Property Search Request Hi, I am interested in buying a flat. Can you please send me the list of available properties in Gota, Ahmedabad? Output Email Example Subject: 🏘️ Property Search Results: 4 Projects Found in Gota, Ahmedabad 🏘️ Available Construction Projects in Gota, Ahmedabad Search Area: Gota, Ahmedabad Total Projects: 4 Search Date: August 4, 2025 📋 PROJECT LISTINGS: 🔷 Project 1 🏠 Name: Vivaan Oliver offers 🏢 BHK: 3 BHK 💰 Price: N/A 📐 Area: 851.0 Sq.Ft 🗓️ Possession: August 2025 📊 Status: under construction 📍 Location: Thaltej, Ahmedabad West 🕒 Scraped Date: 2025-08-04 🔷 Project 2 🏠 Name: Vivaan Oliver offers 🏢 BHK: 3 BHK 💰 Price: Price on Request 📐 Area: 891 Sq Ft 🗓️ Possession: N/A 📊 Status: Under Construction 📍 Location: Thaltej, Ahmedabad West 🕒 Scraped Date: 2025-08-04 🔷 Project 3 🏠 Name: It offers an exclusive range of 🏢 BHK: 3 BHK 💰 Price: N/A 📐 Area: 250 Sq.Ft 🗓️ Possession: 0 2250 📊 Status: Under Construction 📍 Location: Thaltej, Ahmedabad West 🕒 Scraped Date: 2025-08-04 🔷 Project 4 🏠 Name: N/A 🏢 BHK: 2 BHK 💰 Price: N/A 📐 Area: N/A 🗓️ Possession: N/A 📊 Status: N/A 📍 Location: Thaltej, Ahmedabad West 💡 Next Steps: • Contact builders directly for detailed pricing and floor plans • Schedule site visits to shortlisted properties • Verify possession timelines and construction progress • Compare amenities and location advantages 📞 For more information or specific requirements, reply to this email. How to use Setup Instructions Import the workflow into your n8n instance Configure Email Credentials: Set up email trigger for incoming property requests Set up SMTP credentials for sending property listings Configure Web Scraping: Ensure proper headers and user agents for 99acres access Set up fallback mechanisms for different property websites Test the workflow with sample property search emails Sending Property Search Requests Send an email to your configured property search address Include location details in natural language (e.g., "Gota, Ahmedabad") Optionally specify preferences like BHK, budget, or amenities Receive detailed property listings within minutes Requirements n8n instance** (cloud or self-hosted) with web scraping capabilities Email account** with IMAP/SMTP access for automated communication Reliable internet connection** for real-time property data scraping Valid target websites** (99acres, MagicBricks, etc.) access Troubleshooting No properties found**: Verify area spelling and check if the location has active listings Scraping errors**: Update user agents and headers if websites block requests Duplicate results**: Implement better deduplication logic based on property names and locations Email parsing issues**: Test with various email formats and improve regex patterns Website structure changes**: Implement fallback parsers and regular monitoring of scraping success rates. An n8n automation workflow template by Oneclick AI Squad.

By Oneclick AI Squad

This n8n workflow monitors and alerts you about new construction projects in specified areas, helping you track competing builders and identify business opportunities. The system automatically searches multiple data sources and sends detailed email reports with upcoming projects. Good to know Email parsing accuracy depends on the consistency of request formats - use the provided template for best results. The workflow includes fallback mock data for demonstration when external APIs are unavailable. Government data sources may have rate limits - the workflow includes proper error handling. Results are filtered to show only upcoming/recent projects (within 3 months). How it works Email Trigger** - Detects new email requests with "Construction Alert Request" in the subject line Check Email Subject** - Validates that the email contains the correct trigger phrase Extract Location Info** - Parses the email body to extract area, city, state, and zip code information Search Government Data** - Queries government databases for public construction projects and permits Search Construction Sites** - Searches construction industry databases for private projects Process Construction Data** - Combines and filters results from both sources, removing duplicates Wait For Data** - Wait for Combines and filters results. Check If Projects Found** - Determines whether to send a results report or no-results notification Generate Email Report** - Creates a professional HTML email with project details and summaries Send Alert Email** - Delivers the construction project report to the requester Send No Results Email** - Notifies when no projects are found in the specified area The workflow also includes a Schedule Trigger that can run automatically on weekdays at 9 AM for regular monitoring. Email Format Examples Input Email Format To: alerts@yourcompany.com Subject: Construction Alert Request Area: Downtown Chicago City: Chicago State: IL Zip: 60601 Additional notes: Looking for commercial projects over $1M Alternative format: To: alerts@yourcompany.com Subject: Construction Alert Request Please search for construction projects in Miami, FL 33101 Focus on residential and mixed-use developments. Output Email Example Subject: 🏗️ Construction Alert: 8 Projects Found in Downtown Chicago 🏗️ Construction Project Alert Report Search Area: Downtown Chicago Report Generated: August 4, 2024, 2:30 PM 📊 Summary Total Projects Found: 8 Search Query: Downtown Chicago IL construction permits 🔍 Upcoming Construction Projects New Commercial Complex - Downtown Chicago 📍 Location: Downtown Chicago | 📅 Start Date: March 2024 | 🏢 Type: Mixed Development Description: Mixed-use commercial and residential development Source: Local Planning Department Office Building Construction - Chicago 📍 Location: Chicago, IL | 📅 Start Date: April 2024 | 🏢 Type: Commercial Description: 5-story office building with retail space Source: Building Permits [Additional projects...] 💡 Next Steps • Review each project for potential competition • Contact project owners for partnership opportunities • Monitor progress and timeline changes • Update your competitive analysis How to use Setup Instructions Import the workflow into your n8n instance Configure Email Credentials: Set up IMAP credentials for receiving emails Set up SMTP credentials for sending alerts Test the workflow with a sample email Set up scheduling (optional) for automated daily checks Sending Alert Requests Send an email to your configured address Use "Construction Alert Request" in the subject line Include location details in the email body Receive detailed project reports within minutes Requirements n8n instance** (cloud or self-hosted) Email account** with IMAP/SMTP access Internet connection** for API calls to construction databases Valid email addresses** for sending and receiving alerts API Integration Code Examples Government Data API Integration // Example API call to USA.gov jobs API const searchGovernmentProjects = async (location) => { const response = await fetch('https://api.usa.gov/jobs/search.json', { method: 'GET', headers: { 'Content-Type': 'application/json', }, params: { keyword: 'construction permit', location_name: location, size: 20 } }); return await response.json(); }; Construction Industry API Integration // Example API call to construction databases const searchConstructionProjects = async (area) => { const response = await fetch('https://www.construction.com/api/search', { method: 'GET', headers: { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', 'Accept': 'application/json' }, params: { q: ${area} construction projects, type: 'projects', limit: 15 } }); return await response.json(); }; Email Processing Function // Extract location from email content const extractLocationInfo = (emailBody) => { const lines = emailBody.split('\n'); let area = '', city = '', state = '', zipcode = ''; for (const line of lines) { if (line.toLowerCase().includes('area:')) { area = line.split(':')[1]?.trim(); } if (line.toLowerCase().includes('city:')) { city = line.split(':')[1]?.trim(); } if (line.toLowerCase().includes('state:')) { state = line.split(':')[1]?.trim(); } if (line.toLowerCase().includes('zip:')) { zipcode = line.split(':')[1]?.trim(); } } return { area, city, state, zipcode }; }; Customizing this workflow Adding New Data Sources Add HTTP Request nodes for additional APIs Update the Process Construction Data node to handle new data formats Modify the search parameters based on API requirements Enhanced Email Parsing // Custom email parsing for different formats const parseEmailContent = (emailBody) => { // Add regex patterns for different email formats const patterns = { address: /(\d+\s+[\w\s]+,\s[\w\s]+,\s[A-Z]{2}\s*\d{5})/, coordinates: /(\d+\.\d+),\s*(-?\d+\.\d+)/, zipcode: /\b\d{5}(-\d{4})?\b/ }; // Extract using multiple patterns // Implementation details... }; Custom Alert Conditions Modify the Check If Projects Found node to filter by: Project value/budget Project type (residential, commercial, etc.) Distance from your location Timeline criteria Advanced Scheduling // Set up multiple schedule triggers for different areas const scheduleConfigs = [ { area: "Downtown", cron: "0 9 * * 1-5" }, // Weekdays 9 AM { area: "Suburbs", cron: "0 14 * * 1,3,5" }, // Mon, Wed, Fri 2 PM { area: "Industrial", cron: "0 8 * * 1" } // Monday 8 AM ]; Integration with CRM Systems Add HTTP Request nodes to automatically create leads in your CRM when high-value projects are found: // Example CRM integration const createCRMLead = async (project) => { await fetch('https://your-crm.com/api/leads', { method: 'POST', headers: { 'Authorization': 'Bearer YOUR_TOKEN', 'Content-Type': 'application/json' }, body: JSON.stringify({ name: project.title, location: project.location, value: project.estimatedValue, source: 'Construction Alert System' }) }); }; Troubleshooting No emails received**: Check IMAP credentials and email filters Empty results**: Verify API endpoints and add fallback data sources Failed email delivery**: Confirm SMTP settings and recipient addresses API rate limits**: Implement delays between requests and error handling. An n8n automation workflow template by Oneclick AI Squad.

By Mert Dalkır

🛠️ Landing-Page Roast & CRO Ideas Bot – Quick Guide What this workflow does Takes any public landing-page URL. Scrapes the page content. Uses Gemini 2.5-pro to • Roast the page (friendly but brutally honest) • Give 10 high-impact, 2024-ready CRO ideas – all in Turkish, max 3 000 characters. Sends the result back to you on Telegram. Two ways to trigger it Web form • Open the form titled “Conversion Rate Optimizer.” • Paste your landing-page URL(with https or http in front of it). • Click Submit. Telegram (fastest) • Send the URL in a DM to @MertSiteRaporBot. • Forgot the “https://”? No worries—the bot adds it automatically. Behind the scenes • Code node normalises the URL. • HTTP Request scrapes the page HTML. • AI Agent (Gemini) produces the Roast + Recommendations. • Telegram node sends the formatted reply to you. Usage tips • One URL per request. • Page must be publicly accessible (no login). • Very long pages may be trimmed to fit model limits. • Output language is always Turkish. An n8n automation workflow template by Mert Dalkır.

By Jimleuk

Cohere's new multimodal model releases make building your own Vision RAG agents a breeze. If you're new to Multimodal RAG and for the intent of this template, it means to embed and retrieve only document scans relevant to a query and then have a vision model read those scans to answer. The benefits being (1) the vision model doesn't need to keep all document scans in context (expensive) and (2) ability to query on graphical content such as charts, graphs and tables. How it works Page extracts from a technology report containing graphs and charts are downloaded, converted to base64 and embedded using Cohere's Embed v4 model. This produces embedding vectors which we will associate with the original page url and store them in our Qdrant vector store collection using the Qdrant community node. Our Vision RAG agent is split into 2 parts; one regular AI agent for chat and a second Q&A agent powered by Cohere's Command-A-vision model which is required to read contents of images. When a query requires access to the technology report, the Q&A agent branch is activated. This branch performs a vector search on our image embeddings and returns a list of matching image urls. These urls are then used as input for our vision model along with the user's original query. The Q&A vision agent can then reply to the user using the "respond to chat" node. Because both agents share the same memory space, it would be the same conversation to the user. How to use Ensure you have a Cohere account and sufficient credit to avoid rate limit or token usage restrictions. For embeddings, swap out the page extracts for your own. You may need to split and convert document pages to images if you want to use image embeddings. For chat, you may want to structure the agent(s) in another way which makes sense for your environment eg. using MCP servers. Requirements Cohere account for Embeddings and LLM Qdrant for vector store. An n8n automation workflow template by Jimleuk.

By Charles

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 📬 Magic Inbox P2P for n8n — ✨ Instantly Teleport Workflows Magic Inbox is the simplest, most powerful way to TELEPORT your workflows, messages, or files between any two n8n instances — instantly, securely, and with no central server. All you need: A Magic Inbox receiver ("Inbox" node, webhook trigger) A Magic Inbox sender ("Send" node, transformer) A trusted peer’s webhook URL — and the magic happens! ✨ Teleport Your Automation 🚀 Click, Send, Teleport: Send a workflow or any file to another n8n, anywhere in the world, with a single node. 🪄 No cloud, no barriers: Pure peer-to-peer transfer. Your workflow arrives instantly and privately on the recipient's machine, ready-to-use and auto-imported if you wish. 🔁 Collaborate with your team: Share, delegate, or migrate automations on demand, without manual copy-paste or API scripting. 🔹 Features 📤 Teleport workflows, files, and secure messages P2P between n8n servers 📬 Receive and auto-import (optional) any incoming workflow — no extra steps! ⚡️ Works across docker, cloud, self-hosted — anywhere n8n runs 🔐 Whitelist option: restrict trusted senders 🔄 Simple vs Advanced: auto-import for speed, raw mode for power users 🛠️ Installation npm: npm install n8n-nodes-magic-inbox Docker volume: cd /var/lib/docker/volumes/n8n_data/_data/nodes/ npm install n8n-nodes-magic-inbox docker restart 🚦 Usage: Teleport in 3 Steps Create a workflow on n8n-A with your favorite nodes Add Magic Inbox Send. Set "Destination Magic Inbox URL" to your teammate’s or other n8n’s Inbox node webhook. Choose content type: Workflow + Message for teleportation. On n8n-B: Add and enable a Magic Inbox node (receiver) in any workflow. When you hit “Send” on n8n-A, your workflow is instantly delivered/teleported! Auto-import enabled? The workflow appears, active, in the recipient’s n8n — like magic 🪄 ⚙️ Main Parameters Destination Magic Inbox URL: Where to teleport your automation (recipient's webhook). Workflow JSON: Paste the full export from n8n’s workflow page (no manual API!). Auto Import: If enabled, new workflows are instantly usable by the recipient. Whitelist: Allow only trusted emails/IDs as senders. 📝 Example — Teleport a Workflow On n8n-A: Export your workflow as JSON (from the workflow menu) Use Magic Inbox Send with destination URL from n8n-B’s Inbox node Attach the exported JSON and an optional message On n8n-B: Magic Inbox node receives, parses, and (optionally) auto-imports the workflow into your library No code, no copy-paste, no cloud — just teleport! 🐞 Bug Report / Contribute Email : ccharleslepoittevin34@gmail.com 📜 License MIT © Charles Magic Dev 🎁 Magic Dev 📋 1. Presentation and Prerequisites - Quick Without Blabla Essential: manual trigger + n8n-nodes-magic-dev 🤖 Magic Mapping → A prompt, instance URL, N8N API key, OpenRouter API to teleport your workflow to your instance. 🎁 Creator Mapping → Instance URL, N8N API key and a random creator workflow teleports to your instance. 🔑 Quest Mapping → Instance URL, N8N API key, secret code found in Creator Mapping to win a premium workflow. 🗃️ Magic Market: PUBLISH — Share your workflow with a public Google Sheets URL. SEARCH — Find workflows to teleport by keyword in our community database. ⚠️ REQUIRED! Your Google Sheet must have a column named WORKFLOW (all caps, no spaces). Do not use any other column name — otherwise mapping and teleportation will fail. Each row must contain a single n8n workflow as a JSON string in that column. Always check the column header before using Magic Market Teleport! ⭐ FEEDBACK: Optional rating system (1-20 stars) + comments available in all modes 🤝 Creators: Want to collaborate? Contact me via Telegram @magicdev_bot! 💝. An n8n automation workflow template by Charles.

By plemeo

Who’s it for Recruiters, B2B marketers, and thought-leadership builders who want to boost their LinkedIn engagement by automatically liking fresh, relevant posts—while staying under LinkedIn’s daily limits. How it works / What it does Schedule Trigger runs hourly at a specified minute. Select Cookie chooses a rotating LinkedIn session-cookie (time-slice logic). Generate Random Search Term (GPT-4o) outputs a realistic AI/BPA keyword. Phantombuster LinkedIn Content Search Agent scrapes recent posts → Get Posts. Get Random Post selects one post, checks it isn’t already liked (SharePoint CSV) and appends the company-ID query param. If a personal LinkedIn Account is used, no company-ID is needed. Creates linkedin_posts_to_like.csv, uploads to SharePoint, and provides the URL to Autolike Agent which likes the post. The post URL is added to linkedin_posts_already_liked.csv to avoid duplicates. Wait nodes throttle launches to ≈400 likes/day. How to set up Add credentials: Phantombuster API, SharePoint OAuth2, OpenAI API key. In SharePoint › “Phantombuster” folder create: • linkedin_session_cookies.txt – one cookie per line. • linkedin_posts_already_liked.csv with header postUrl. Update Set ENV Variables with your LinkedIn company ID (ENV_COMPANY_ID_LINKEDIN). Adjust schedule or likes-per-launch as needed. Activate the workflow; it will run hourly and like one new post per launch. Requirements n8n 1.33 + Phantombuster Growth plan (API access) OpenAI account (GPT-4o) Microsoft 365 SharePoint tenant How to customize Change niche: edit the prompt in Generate Random Search Term. Like more posts: raise numberOfLinesPerLaunch and schedule frequency. Swap SharePoint for Google Drive/Dropbox: replace the upload/download nodes. An n8n automation workflow template by plemeo.

By Stephan Koning

Real-Time ClickUp Time Tracking to HubSpot Project Sync This workflow automates the synchronization of time tracked on ClickUp tasks directly to a custom project object in HubSpot, ensuring your project metrics are always accurate and up-to-date. Use Case & Problem This workflow is designed for teams that use a custom object in HubSpot for high-level project overviews (tracking scoped vs. actual hours per sprint) but manage daily tasks and time logging in ClickUp. The primary challenge is the constant, manual effort required to transfer tracked hours from ClickUp to HubSpot, a process that is both time-consuming and prone to errors. This automation eliminates that manual work entirely. How It Works Triggers on Time Entry:** The workflow instantly starts whenever a user updates the time tracked on any task in a specified ClickUp space. ⏱️ Fetches Task & Time Details:** It immediately retrieves all relevant data about the task (like its name and custom fields) and the specific time entry that was just updated. Identifies the Project & Sprint:** The workflow processes the task data to determine which HubSpot project it belongs to and categorizes the work into the correct sprint (e.g., Sprint 1, Sprint 2, Additional Requests). Updates HubSpot in Real-Time:** It finds the corresponding project record in HubSpot and updates the master actual_hours_tracked property. It then intelligently updates the specific field for the corresponding sprint (e.g., actual_sprint_1_hours), ensuring your reporting remains granular and accurate. Requirements ✅ ClickUp Account with the following custom fields on your tasks: A Dropdown custom field named Sprint to categorize tasks. A Short Text custom field named HubSpot Deal ID or similar to link to the HubSpot record. ✅ HubSpot Account with: A Custom Object used for project tracking. Custom Properties** on that object to store total and sprint-specific hours (e.g., actual_hours_tracked, actual_sprint_1_hours, total_time_remaining, etc.). > Note: Since this workflow interacts with a custom HubSpot object, it uses flexible HTTP Request nodes instead of the standard n8n HubSpot nodes. Setup Instructions Configure Credentials: Add your ClickUp (OAuth2) and HubSpot (Header Auth with a Private App Token) credentials to the respective nodes in the workflow. Set ClickUp Trigger: In the Time Tracked Update Trigger node, select your ClickUp team and the specific space you want to monitor for time updates. Update HubSpot Object ID: Find the ID of your custom project object in HubSpot. In the HubSpot HTTP Request nodes (e.g., OnProjectFolder), replace the placeholder ID objectTypeId in the URL with your own objectTypeId How to Customize Adjust the Code: Extract Sprint & Task Data node to change how sprint names are mapped or how time is calculated. Update the URLs in the HubSpot HTTP Request nodes if your custom object or property names differ. An n8n automation workflow template by Stephan Koning.

By Adrian Kendall

Summary This is a minimal template that focuses on how to integrate n8n and Home Assistant for event-based triggering from Home Assistant using the AppDaemon addon to call a webhook node. Problem Solved: There is no Home Assistant trigger node in n8n. You can poll the Home Assistant API on a schedule. A more efficient work around is to use the AppDaemon addon to create a listener app within Home Assistant. When the listener detects the event, it is subscribed to. An AppDaemon app is initiated that calls a N8N webhook passing the the event data to the workflow. AppDaemon runs python code. The template contains a sticky note. Within the sticky note there is a code example (repeated below) for a AppDeamon app, the code contains annotated instructions on configuration. Steps: Install the AppDaemon Add-on A. Open Home Assistant. In your Home Assistant UI, go to Settings - Add-ons (or Supervisor - Add-on Store, depending on your version). B. Search and Install. In the Add-on Store, search for "AppDaemon 4". Click on the result and then the Install button to start the installation. C. Start the Add-on. Once installed, open the AppDaemon 4 add-on page. Click Start to launch AppDaemon. (Optional but recommended) Enable Start on boot and Watchdog options to make sure AppDaemon starts automatically and restarts if it crashes. D. Verify Installation. Check the logs in the AppDaemon add-on page to ensure it’s running without issues. No need to set access tokens or Home Assistant URL manually; the add-on is pre-configured to connect with your Home Assistant. E. Configure AppDaemon. After installation, a directory named appdaemon will appear inside your Home Assistant config directory (/config/appdaemon/). Inside, you’ll find a file called appdaemon.yaml. For most uses, the default configuration is fine, but you can customize it as needed. Create the AppDaemon App. F. Prepare Your Apps Directory. Inside /config/appdaemon/, locate or create an apps folder. Path: /config/appdaemon/apps/. G. Create a Python App Inside the apps folder, create a new Python file (example: n8n_WebHook.py). Open the file in an editor and paste the example code into the file. import appdaemon.plugins.hass.hassapi as hass import requests import json class EventTon8nWebhook(hass.Hass): """ AppDaemon app that listens for Home Assistant events and forwards them to n8n webhook """ def initialize(self): """ Initialize the event listener and configure webhook settings """ EDIT: Replace 'your_event_name' with the actual event you want to listen for Common HA events: 'state_changed', 'call_service', 'automation_triggered', etc. self.target_event = self.args.get('target_event', 'your_event_name') EDIT: Set your n8n webhook URL in apps.yaml or replace the default here self.webhook_url = self.args.get('webhook_url', 'n8n_webhook_url') EDIT: Optional - set timeout for webhook requests (seconds) self.webhook_timeout = self.args.get('webhook_timeout', 10) EDIT: Optional - enable/disable SSL verification self.verify_ssl = self.args.get('verify_ssl', True) Set up the event listener self.listen_event(self.event_handler, self.target_event) self.log(f"Event listener initialized for event: {self.target_event}") self.log(f"Webhook URL configured: {self.webhook_url}") def event_handler(self, event_name, data, kwargs): """ Handle the triggered event and forward to n8n webhook Args: event_name (str): Name of the triggered event data (dict): Event data from Home Assistant kwargs (dict): Additional keyword arguments from the event """ try: Prepare payload for n8n webhook payload = { 'event_name': event_name, 'event_data': data, 'event_kwargs': kwargs, 'timestamp': self.datetime().isoformat(), 'source': 'home_assistant_appdaemon' } self.log(f"Received event '{event_name}' - forwarding to n8n") self.log(f"Event data: {data}") Send to n8n webhook self.send_to_n8n(payload) except Exception as e: self.log(f"Error handling event {event_name}: {str(e)}", level="ERROR") def send_to_n8n(self, payload): """ Send payload to n8n webhook Args:payload (dict): Data to send to n8n """ try: headers = { 'Content-Type': 'application/json', #EDIT assume header authentication parameter and value below need to match what is set in the credential used in the node. 'CredName': 'credValue', #set to what you set up as a credential for the webhook node } response = requests.post( self.webhook_url, json=payload, headers=headers, timeout=self.webhook_timeout, verify=self.verify_ssl ) response.raise_for_status() self.log(f"Successfully sent event to n8n webhook. Status: {response.status_code}") EDIT: Optional - log response from n8n for debugging if response.text: self.log(f"n8n response: {response.text}") except requests.exceptions.Timeout: self.log(f"Timeout sending to n8n webhook after {self.webhook_timeout}s", level="ERROR") except requests.exceptions.RequestException as e: self.log(f"Error sending to n8n webhook: {str(e)}", level="ERROR") except Exception as e: self.log(f"Unexpected error sending to n8n: {str(e)}", level="ERROR") H. Register Your App In the same apps folder, locate or create a file named apps.yaml. Add an entry to register your app: EventTon8nWebhook: module: n8n_WebHook class: EventTon8nWebhook Module should match your Python filename (without the .py). class matches the class name inside your Python file, i.e. EventTon8nWebHook I. Reload AppDaemon In Home Assistant, return to the AppDaemon 4 add-on page and click Restart. Watch the logs; you should see a log entry from your app confirming it is initialised running. Set Up n8n J. In your workflow create a webhook trigger node as the first node, or use the template as your starting point. Ensure the webhook URL (production or test) is correctly copied to the python code. If you are using authentication this needs a credential creating for the webhook. The example uses header auth. Naturally this should match what is in the code. For security likely better to put the credentials in a "secrets.yaml" file rather than hard code like this demo. Execute the workflow or activate if using the production webhook. Either wait for an event in Home Assistant or one can be manually triggered from the developer settings page, event tab. K. Finally develop your workflow to process the received event per your use case. See the Home Assistant docs on events for details of the event types you can subscribe to: Home Assistant Events. An n8n automation workflow template by Adrian Kendall.

By Halfbit 🚀

Jura Coffee Counter: Webhook API & Google Sheets Logger ☕️ Track how many coffees your Jura E8 espresso machine makes — fully automated via webhook and Google Sheets. This workflow exposes a custom API endpoint that can be called by smart devices, such as an ESP8266 or ESP32 reading data from a Jura E8 coffee machine via Bluetooth Low Energy (BLE). The incoming data (including total coffee count) is timestamped and appended to a Google Sheet, making it easy to visualize or analyze your machine usage. ☕ Originally built for a Jura E8, based on AlexxIT/Jura reverse-engineering project. > 📝 This workflow uses Google Sheets as a logging backend. You can easily switch it to Airtable, Notion, or a database of your choice. Live example available at: https://halfbitstudio.com/o-nas/ > 🖥️ In our setup, this workflow is used to provide real-time coffee consumption stats displayed directly on our website. > 🔌 Some Jura machines require an accessory Bluetooth transmitter to enable connectivity. Communication is based on the Bluetooth Low Energy (BLE) protocol. Use Case Tracking usage of a Jura coffee machine Logging IoT sensor data into Google Sheets Creating dashboards for daily consumption Smart office setups with coffee stats! Features ☁️ Two Webhook endpoints: POST /{{WEBHOOK_POST_PATH}} — receives JSON from ESP (coffee machine reader) GET /{{WEBHOOK_GET_PATH}} — returns latest records as JSON 📅 Timestamping via Date & Time node 🔹 Coffee counter extraction from incoming JSON 🧾 Appends structured rows to Google Sheets 📤 Webhook response for external status or dashboards Setup Instructions Jura Coffee Machine Integration (Hardware) Use an ESP device (e.g. ESP8266 or ESP32) to connect to the Jura E8 via Bluetooth Low Energy (BLE). Send POST requests with JSON payload: { "total_coffees": 123 } Reverse-engineered protocol reference: AlexxIT/Jura Google Sheets Configuration Create a new Google Sheet with column headers like: date | time | coffee counter Connect your Google account in n8n and authorize access to this sheet. Replace the documentId and sheetName fields in the Google Sheets nodes: Use full URL to your spreadsheet Use the actual sheet name (e.g. Sheet1) Environment Variables & Placeholders | Placeholder | Description | | ------------------------ | ----------------------------------------------- | | {{WEBHOOK_POST_PATH}} | Endpoint to receive coffee counter data | | {{WEBHOOK_GET_PATH}} | Endpoint to return latest data (for dashboards) | | {{SHEET_ID}} | Google Spreadsheet ID | | {{GOOGLE_CREDENTIALS}} | OAuth2 credentials for Google Sheets | | {{DATA_COLUMNS}} | Column names in the target sheet | Testing the Workflow Send test request: Use Postman or ESP to send a POST request to /{{WEBHOOK_POST_PATH}} Body should include total_coffees value Check Google Sheet: Open your sheet and verify that a new row was appended Test GET endpoint: Access the second webhook URL (e.g. /{{WEBHOOK_GET_PATH}}) in browser or fetch via API Optional: Use Respond to Webhook output in a dashboard or frontend Customization Tips Sheet format**: Add more columns if you want to track additional data (e.g. machine temperature, errors) Output format**: Replace Google Sheets with any other storage (e.g. MySQL, Notion) Auth layer**: Add basic auth or token verification if needed for public exposure Notifications**: Send alerts to Discord/Slack when reaching thresholds (e.g. 200 coffees brewed) Tags: google-sheets, iot, webhook, jura, coffee, api, automation. An n8n automation workflow template by Halfbit 🚀.