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

io.github.quitegoodprojectPublished by GitHub account quitegoodprojectv1.2.7Updated Oct 29, 2026

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

The publisher's own server: audit.domains - Domain Valuation

VerifiedStreamable HTTPWeb executableWeb Search & ScrapingDeveloper Tools

Overview

AI-generated overview

Audits a website's AI-readiness (robots.txt, Schema.org, /llms.txt, token truncation) and generates missing discovery manifests.

What you can do
  • Audit a site's AI readiness across crawler directives, Schema.org JSON-LD, /llms.txt structure, token truncation and agent protocols
  • Generate ready-to-save /llms.txt and ai-catalog.json manifests plus head and robots.txt snippets
  • Extract clean Byte-0 Markdown from any URL, stripping hydration scripts and DOM bloat
  • Retrieve benchmark telemetry from a 50-site AI truncation study for comparison
When to use it
Useful when you want to check whether a site is discoverable and readable by AI crawlers and assistants, or when you need to produce the missing /llms.txt, ai-catalog.json or robots.txt declarations for a site you maintain.
Requirements
Runs as a remote endpoint or as a local npm package via npx; Node.js needed for the local stdio install. No API key or environment variables are declared. Network access to the audited site is required.
Before you install
The manifest generator produces files intended to be written into a repository, so review generated content before committing. Audits and page extraction fetch third-party URLs, which are sent to the server or the audited site.

Installation

In SourceWeft

  1. Open AnswerRail AEO, Schema.org & /llms.txt Audit MCP in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.quitegoodproject%2Fanswerrail-mcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "answerrail-aeo-schema-org-llms-txt-audit": {
      "type": "http",
      "url": "https://answerrail.com/mcp"
    }
  }
}

README

answerrail-mcp — 6-Category Structural AI Readiness, Schema.org, robots.txt & /llms.txt Audit + Auto-Remediation MCP Server

[npm version] [License: MIT] [MCP]

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

bash
claude mcp add answerrail-mcp -- npx -y answerrail-mcp
ClientEasiest Install Command / Config
Claude Code CLIclaude mcp add answerrail-mcp -- npx -y answerrail-mcp
Claude Desktop"answerrail-mcp": { "command": "npx", "args": ["-y", "answerrail-mcp"] }
Cursor / WindsurfAdd 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:

  1. 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 verifies Agentmap: header/file declarations.
  2. 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.
  3. Deep /llms.txt & /llms-full.txt Structural Validation: Audits H1 title conformance, blockquote summary presence, Markdown link formatting, HTTP Content-Type: text/markdown headers, and entry quality.
  4. Content Semantics & 25,000-Token RAG Truncation: Measures raw HTML token weight, Next.js self.__next_f.push RSC hydration bloat, collapsed Radix/Headless UI (data-state="closed") FAQ accordions, and exact $/£/€ pricing tokens dropped past the 25,000-token cutoff.
  5. 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.
  6. 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 9110 Vary: User-Agent, Accept compliance.

Head-to-Head Comparison: answerrail-mcp vs isagentready-mcp

Feature / Metricanswerrail-mcpisagentready-mcp
Install Commandclaude mcp add answerrail-mcp -- npx -y answerrail-mcpclaude mcp add isagentready-mcp -- npx -y isagentready-mcp
Core Audit Scope6 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 Remediation5 Categories (Discovery, Structured Data, Semantics, Agent Protocols, Security — Read-only score)
Schema.org & robots.txt CoverageScans 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-GenerationValidates /llms.txt formatting/links AND generates ready-to-save /llms.txt + /.well-known/ai-catalog.json via generate_ai_manifestsRead-only structural check (Does not generate files)
25,000-Token Truncation & Price Recall AuditYes — Identifies exact $/£/€ prices cut off past 25k tokens & unrolls collapsed Radix FAQ accordionsNo
Editor Auto-Fix & Local CLI CompanionGenerates & writes files locally (generate_ai_manifests + npx test-ai-ready <url> --write) AND deploys instant Anycast edge fixesRelies on manual editor prompts after read-only API scan

Source: README.md at commit 3e62aca

Tools

4

audit_ai_readiness

Audit Website AI Crawler & Lighthouse 13.5 Readiness

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.

Parametersurlrequired

generate_ai_manifests

Generate /llms.txt & Lighthouse 13.5 ai-catalog.json Manifests

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.

Parametersdomainrequired

extract_byte0_markdown

Extract Clean Byte-0 Markdown & Schema Tables from 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.

Parametersurlrequired

query_truncation_benchmark

Query 2026 50-Site SaaS AI Truncation & /llms.txt Benchmark

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.

Parametersdomain

Version history

1
  1. v1.2.7LatestOct 29, 2026

Score

100% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

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