Glintbase

Description

# Glintbase MCP Server (ARS 3.0) **Glintbase** is the open audit and simulation standard for the autonomous AI agent web. It gives AI coding agents (Claude Code, Cursor, Windsurf, Devin, Antigravity) empirical visibility into whether a website, developer portal, or API is truly agent-ready—or full of silent friction, 404 traps, and schema hallucinations. Built on the **Agent Readiness Score (ARS 3.0)** specification, this MCP server provides instant surface discovery, lightweight scorecards, flight simulation with visual SVG telemetry, and 9 bundled remediation playbooks. --- ## ✨ Features - **Empirical ARS 3.0 Scoring**: Evaluates domains across 6 core pillars: *Discovery*, *Access*, *Usability*, *Semantic*, *Architecture*, and *Safety*. - **Machine Surface Discovery**: Automatically detects and validates `robots.txt` AI policies, `/llms.txt`, `/llms-full.txt`, `/.well-known/ard.json`, `/auth.md`, and OpenAPI specifications. - **Visual Flight Simulator**: Simulates synthetic coding personas (Claude Code, Cursor, Perplexity) executing developer journeys, outputting visual SVG journey trees, schema friction metrics, and token-tax telemetry. - **Context-Preserving Scores**: Fetch ultra-compact scorecards in under 200 tokens to preserve agent context windows during automated workflows. - **9 Bundled Playbooks**: Instant access to complete ARS 3.0 remediation manuals (living artifacts, WorkOS auth contracts, streamable MCP servers, and CI gates). --- ## 🛠️ Tools | Tool | Parameters | Description | | :--- | :--- | :--- | | `glintbase_audit` | `target` (string) | Runs a complete 119-check ARS 3.0 audit on any target URL. Returns detailed layer breakdowns, passed/failed checks, and actionable remediation diffs. | | `glintbase_get_score` | `target` (string) | Returns an ultra-compact score card (<200 tokens) with letter grade, archetype classification, and layer scores. Ideal for rapid CI checks. | | `glintbase_discover_surfaces` | `target` (string) | Scans and maps all machine entrypoints (`robots.txt`, `llms.txt`, `ard.json`, `auth.md`, OpenAPI, sitemap). | | `glintbase_simulate_flight` | `target` (string), `persona` (enum: `claude-code`, `cursor`, `perplexity`), `intent` (string) | Runs an autonomous mission simulation. Returns step-by-step navigation telemetry, token consumption, and a visual SVG journey tree graphic. | | `glintbase_get_skill` | `skillName` (string) | Retrieves full, multi-step ARS 3.0 remediation playbooks (e.g. `agent-readiness`, `living-artifacts`, `agent-auth`, `mcp-hardening`). | *Note: All tools support both `glintbase_*` names and canonical short names (`audit`, `get_score`, `discover_surfaces`, `simulate_flight`, `get_skill`).* --- ## 📚 Bundled Prompts & Resources ### Prompts - `optimize_agent-readiness`: Master workflow for elevating a codebase to ARS 3.0 standards. - `optimize_living-artifacts-architect`: Step-by-step guidance for authoring `llms.txt`, `llms-full.txt`, and `ard.json`. - `optimize_agent-auth-handbook`: Blueprint for RFC 9728 machine-to-machine authentication contracts (`auth.md`). - `optimize_streamable-mcp-builder`: Architectural guide for deploying streamable HTTP MCP servers. - `optimize_flight-simulator-replay`: Diagnostic playbook for analyzing agent bottlenecks. ### Resources - `skill://glintbase/agent-readiness`: Master ARS 3.0 Playbook. - `skill://glintbase/living-artifacts`: Living Artifacts Specification. - `skill://glintbase/agent-auth`: Agent Authentication Handbook. - `glintbase://schemas/ars3-spec`: Complete ARS 3.0 evaluation schema. - `glintbase://standards/auth-contract`: RFC 9728 machine auth template. --- ## 🚀 Quick Start ### Option A: Smithery CLI ```bash npx -y @smithery/cli install @glintbase/mcp --client claude

Community Metrics

Categories

• mcp

Tags

• mcp
• smithery

Capabilities

• Remote MCP server

Information