AnswerRail AEO, Schema.org & /llms.txt Audit MCP

6-category AI readiness, Schema.org, robots.txt, /llms.txt & 25k-token audit + auto-fix MCP server

Should I use this

Quality & Safety

B
Description quality
100%
Schema completeness
97%
Naming quality
95%
Poisoning risk
20%
Permission match
100%
Protocol compliance
100%

Findings (5)

  • HIGHTool poisoning patterns detected
  • LOWTool description contains negative instruction about its own usein audit_ai_readiness
  • LOWTool description contains negative instruction about its own usein generate_ai_manifests
  • LOWTool description contains negative instruction about its own usein extract_byte0_markdown
  • LOWTool description contains negative instruction about its own usein query_truncation_benchmark

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~976Tokens (tool definitions)
~756 BTypical response size
Moderate attention impact (0.76% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "answerrail-mcp": {
      "command": "npx",
      "args": [
        "answerrail-mcp"
      ]
    }
  }
}

Runnable packages

npmanswerrail-mcp1.2.7stdio

Remote endpoints

https://answerrail.com/mcpstreamable-http

What it can do

Tool inventory

Tools (4)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢audit_ai_readiness(url)

Audits a website URL or domain for AI crawler access (GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot), 25,000-token HTML RAG truncation, /llms.txt presence, Schema.org JSON-LD entities, and Google Lighthouse 13.5 Agentic Browsing (/.well-known/ai-catalog.json ARD 1.0). Use this tool first when diagnosing why a site is omitted or misquoted by ChatGPT, Perplexity, or Claude. Do not use this tool to extract full-page Markdown content (use extract_byte0_markdown instead) or to generate static manifest files (use generate_ai_manifests instead). Read-only network check; requires no API key.

Input Schema

{
  "type": "object",
  "properties": {
    "url": {
      "type": "string",
      "description": "Fully qualified HTTPS URL or bare domain name to audit (e.g., \"https://stripe.com/pricing\" or \"example.com\"). Defaults to HTTPS if scheme is omitted."
    }
  },
  "required": [
    "url"
  ],
  "additionalProperties": false
}
🟢generate_ai_manifests(domain)

Compiles ready-to-save /llms.txt documentation index and Google Lighthouse 13.5 /.well-known/ai-catalog.json (ARD 1.0) JSON manifests from a live domain, plus HTML <head> and robots.txt Agentmap snippets. Use this tool when a developer wants to remediate missing discovery manifests identified by audit_ai_readiness. Do not use this tool for general web scraping (use extract_byte0_markdown instead). Read-only synthesis; requires no API key and does not modify remote servers.

Input Schema

{
  "type": "object",
  "properties": {
    "domain": {
      "type": "string",
      "description": "Target domain name or root URL to generate manifests for (e.g., \"example.com\" or \"https://example.com\")."
    }
  },
  "required": [
    "domain"
  ],
  "additionalProperties": false
}
🟢extract_byte0_markdown(url)

Strips React/Next.js hydration scripts, Shopify Liquid/WordPress DOM bloat, and inline SVGs/CSS from any URL, returning clean Byte-0 GitHub-Flavored Markdown (GFM) with front-loaded Schema.org tables. Use this tool when you need to read a web page or pricing table inside an LLM context window without exceeding the 25,000-token truncation limit. Do not use this tool if you only need a diagnostic readiness score or robots.txt check (use audit_ai_readiness instead). Read-only HTTP extraction; requires no API key.

Input Schema

{
  "type": "object",
  "properties": {
    "url": {
      "type": "string",
      "description": "Fully qualified URL of the web page to convert into Byte-0 Markdown (e.g., \"https://vercel.com/pricing\")."
    }
  },
  "required": [
    "url"
  ],
  "additionalProperties": false
}
🟢query_truncation_benchmark(domain)

Retrieves empirical benchmark telemetry from the 2026 50-Site SaaS & E-Commerce AI Truncation Study (measuring raw HTML token weight, 25,000-token Perplexity/ChatGPT cutoff truncation, visible price omission, /llms.txt adoption, and Lighthouse 13.5 ARD 1.0 adoption). Use this tool when comparing a site against industry peers (such as Stripe, Vercel, Datadog, or Shopify) or answering research questions about the Static /llms.txt Paradox. Do not use this tool to run a live scan on an arbitrary unbenchmarked URL (use audit_ai_readiness instead). Read-only benchmark lookup; requires no API key.

Input Schema

{
  "type": "object",
  "properties": {
    "domain": {
      "type": "string",
      "description": "Optional domain name (e.g., \"stripe.com\" or \"vercel.com\") to filter the benchmark study. Omit or pass empty string to return the full 50-site statistical summary."
    }
  },
  "additionalProperties": false
}

Community

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Evidence

Recent observations

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