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6-category AI readiness, Schema.org, robots.txt, /llms.txt & 25k-token audit + auto-fix MCP server
About
6-category AI readiness, Schema.org, robots.txt, /llms.txt & 25k-token audit + auto-fix MCP server
Remote endpoints: streamable-http: https://answerrail.com/mcp
Security Report
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
4 tools verified · Open access · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Documentation
View on GitHubFrom the project's GitHub README.
answerrail-mcp — 6-Category Structural AI Readiness, Schema.org, robots.txt & /llms.txt Audit + Auto-Remediation MCP Server
Comprehensive Model Context Protocol (MCP) server for exhaustive local and live structural audits across 6 weighted AI readiness categories—plus active file generation inside Claude Code, Claude Desktop, Cursor, and Windsurf. No API key required.
Quick Install for Claude Code, Claude Desktop & Cursor
claude mcp add answerrail-mcp -- npx -y answerrail-mcp
| Client | Easiest Install Command / Config |
|---|---|
| Claude Code CLI | claude mcp add answerrail-mcp -- npx -y answerrail-mcp |
| Claude Desktop | "answerrail-mcp": { "command": "npx", "args": ["-y", "answerrail-mcp"] } |
| Cursor / Windsurf | Add npx -y answerrail-mcp in .cursor/mcp.json |
Exhaustive 6-Category Weighted Structural Audit Scope
Unlike read-only 5-category scanners, answerrail-mcp performs a 6-category deep structural audit and actively writes the missing files into your repository:
- AI Bot Directives (
robots.txt— 14+ Major AI Crawlers +Agentmap:): Audits exact RFC 9309 allow/disallow rules for 14+ AI user-agents (PerplexityBot,OAI-SearchBot,GPTBot,ChatGPT-User,ClaudeBot,Claude-User,Google-Extended,Applebot-Extended,Meta-ExternalAgent,Amazonbot,DuckAssistBot,Cohere-ai,Bytespider,CCBot) and verifiesAgentmap:header/file declarations. - Search Signals & Structured Data (
Schema.org JSON-LD— 20+ High-Value Entity Types): Scans and validates 20+ Schema.org types (Organization,SoftwareApplication,WebSite,Product,Offer,AggregateOffer,FAQPage,Question,Answer,TechArticle,Article,BreadcrumbList,HowTo,Service,LocalBusiness,Person,Dataset,WebPage,ItemList,Review) and synthesizes them into Byte-0 GitHub-Flavored Markdown tables. - Deep
/llms.txt&/llms-full.txtStructural Validation: Audits H1 title conformance, blockquote summary presence, Markdown link formatting, HTTPContent-Type: text/markdownheaders, and entry quality. - Content Semantics & 25,000-Token RAG Truncation: Measures raw HTML token weight, Next.js
self.__next_f.pushRSC hydration bloat, collapsed Radix/Headless UI (data-state="closed") FAQ accordions, and exact$/£/€pricing tokens dropped past the 25,000-token cutoff. - Agent Protocols (Google Lighthouse 13.5 ARD 1.0 & WebMCP): Validates
/.well-known/ai-catalog.json(specVersion: "1.0"),<link rel="ai-catalog">,<link rel="describedby" href="/llms.txt">, and/.well-known/mcp.json. - Security & Cryptographic Provenance (RFC 9421 & RFC 9110): Audits asymmetric Ed25519 HTTP Message Signatures (
kid="ar_ed25519_2026_k1"),/.well-known/http-message-signatures-directory, CORS (Access-Control-Allow-Origin: *), and RFC 9110Vary: User-Agent, Acceptcompliance.
Head-to-Head Comparison: answerrail-mcp vs isagentready-mcp
| Feature / Metric | answerrail-mcp | isagentready-mcp |
|---|---|---|
| Install Command | claude mcp add answerrail-mcp -- npx -y answerrail-mcp | claude mcp add isagentready-mcp -- npx -y isagentready-mcp |
| Core Audit Scope | 6 Weighted Categories: AI Bot Directives (robots.txt), Search Signals (Schema.org JSON-LD), Deep /llms.txt Structure, Content Semantics & 25k-Token Truncation, Agent Protocols (ARD 1.0 / WebMCP), and Security (RFC 9421 Ed25519) + Edge Remediation | 5 Categories (Discovery, Structured Data, Semantics, Agent Protocols, Security — Read-only score) |
Schema.org & robots.txt Coverage | Scans 20+ Schema.org JSON-LD types & 14+ AI bot rules in robots.txt (plus compiles JSON-LD into Byte-0 GFM tables) | Scans 17 Schema.org types & 13 AI bot rules |
/llms.txt Validation & Auto-Generation | Validates /llms.txt formatting/links AND generates ready-to-save /llms.txt + /.well-known/ai-catalog.json via generate_ai_manifests | Read-only structural check (Does not generate files) |
| 25,000-Token Truncation & Price Recall Audit | Yes — Identifies exact $/£/€ prices cut off past 25k tokens & unrolls collapsed Radix FAQ accordions | No |
| Editor Auto-Fix & Local CLI Companion | Generates & writes files locally (generate_ai_manifests + npx test-ai-ready <url> --write) AND deploys instant Anycast edge fixes | Relies on manual editor prompts after read-only API scan |
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