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

by quitegoodprojectversion 1.2.7i★ –iComputer or cloud
Registry nameio.github.quitegoodproject/answerrail-mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 3 of 3 passed
  • Runs on the maker’s server: what you ask it goes through their server.
  • Can do 4 things (tools) audit_ai_readiness, generate_ai_manifests, extract_byte0_markdown, query_truncation_benchmark
  • The registry lists no key to fill in.

You need

  • Runs in the cloudNothing to install; it connects over the internet
  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

  1. Open Settings → Connectors
  2. Press Add custom connector
  3. Paste the address below and press Add
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Add2https://…3
https://answerrail.com/mcp

Or run it on your computer

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

claude mcp add --transport http answerrail https://answerrail.com/mcp

Or run it on your computer

claude mcp add answerrail -- npx -y answerrail-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "answerrail": {
      "url": "https://answerrail.com/mcp"
    }
  }
}

Or run it on your computer

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "answerrail": {
      "type": "http",
      "url": "https://answerrail.com/mcp"
    }
  }
}

Or run it on your computer

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "answerrail": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "answerrail-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

  1. Open ChatGPT on the web → Settings → Connectors (Apps)
  2. Press Create or Add (some plans need Developer mode under Advanced first)
  3. Paste the address below, give it a name and save
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Create2https://…3
https://answerrail.com/mcp

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Tool names and descriptions exactly as the server reported them on Nov 7, 2026. The maker wrote them, not us; we show them as plain text.

  • audit_ai_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

  • generate_ai_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 and robots.txt Agentmap snippets. Use this tool when a developer wants to remediate missing discovery manifests iden

  • extract_byte0_markdown

    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 c

  • query_truncation_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 too

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account quitegoodproject, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • ✓ Pass

    Endpoint responds

    Responded in 464 ms (HTTP 200)

  • – Not applicable

    Sign-in with OAuth

    No sign-in needed

  • ✓ Pass

    No hidden instructions in tool descriptions

    Read 4 tool descriptions and found no hidden instructions to the AI

Compared with others in Otheri

  • More stars than 0% of the other 32715 servers in this category
  • Published to the registry more recently than 79% of the other 32715 servers in this category
  • Basic checks equal to or better than 100% of the other 32715 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

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

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.2.7) reached the registry 9 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, First Sale Scout

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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First Sale Scout

by firstsale.pro

Playbooks and a 14-day checklist for founders winning their first paying customers.

Runs in the cloudUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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
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"), , , 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_manifests`Read-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 --write`) AND deploys instant Anycast edge fixesRelies on manual editor prompts after read-only API scan
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