# AnswerRail AEO, Schema.org & /llms.txt Audit MCP (npm · answerrail-mcp)

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

- Trust score: 71/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-04

## Components

- remote · `answerrail.com`: 73/100, [markdown](https://verifymcp.io/servers/quitegoodproject-answerrail-mcp/answerrail.md), [page](https://verifymcp.io/servers/quitegoodproject-answerrail-mcp/answerrail)
- npm · `answerrail-mcp`: 71/100 (this document), [markdown](https://verifymcp.io/servers/quitegoodproject-answerrail-mcp/answerrail-mcp.md), [page](https://verifymcp.io/servers/quitegoodproject-answerrail-mcp/answerrail-mcp)

## Channel facts

- Registry: `npm`
- Package: `answerrail-mcp`
- Version: `1.2.7`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-11-04.

- **Supply Chain Security**: 100/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - No install/post-install scripts declared.
  - No production dependencies, so there is no dependency health to assess.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 3 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 82/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 968 tokens (~138/item across 7 items; 5 tools + 2 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 20/100
  - Stability observed for 6 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 20/100
  - Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28.

## Install

### How do I install the AnswerRail AEO, Schema.org & /llms.txt Audit MCP server?

AnswerRail AEO, Schema.org & /llms.txt Audit MCP runs locally as an npm package, launched with npx -y answerrail-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add quitegoodproject-answerrail-mcp -- npx -y answerrail-mcp
```

### Cursor

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

### VS Code

```json
{
  "servers": {
    "quitegoodproject-answerrail-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "answerrail-mcp"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add quitegoodproject-answerrail-mcp -- npx -y answerrail-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "quitegoodproject-answerrail-mcp": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "answerrail-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add quitegoodproject-answerrail-mcp --command npx --arg -y --arg answerrail-mcp
```

### Hermes

```yaml
mcp_servers:
  quitegoodproject-answerrail-mcp:
    command: "npx"
    args: ["-y", "answerrail-mcp"]
```

### Netclaw

```json
{
  "McpServers": {
    "quitegoodproject-answerrail-mcp": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "answerrail-mcp"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add quitegoodproject-answerrail-mcp -t stdio -c npx -a -y answerrail-mcp
```

### Other

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

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-11-03 (score 71, +1)

No change was recorded against any check on this day. Stability & Change Management went from 13 to 17. That category is still filling its 30-day observation window: 4 days of observed history at the previous scan, 5 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-31 (score 70, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-10-29 (score 69)

First indexed and scored.

## MCP tools (5)

### `audit_local_codebase_and_generate` (~170 tokens)

Audit Local Codebase (20+ Schema.org & 14+ AI Bot Rules) & Generate /llms.txt + ai-catalog.json

Performs a deep local filesystem structural compliance audit across 6 weighted categories (scanning local robots.txt against 14+ AI crawler directives, scanning local HTML/TSX/JSX files across 20+ Schema.org JSON-LD entity types, validating /llms.txt syntax, and checking ARD 1.0 /.well-known/ai-catalog.json) and actively generates compliant /llms.txt and /.well-known/ai-catalog.json files in the target project directory.

Input parameters:

- `outputAll` (boolean): When true (default), actively writes compliant /llms.txt and /.well-known/ai-catalog.json into public/ or targetDir.
- `targetDir` (string, required): Local project directory path to scan and write manifests into (e.g., "./" or ".").

### `audit_ai_readiness` (~201 tokens)

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.

Input parameters:

- `url` (string, required): 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.

### `generate_ai_manifests` (~147 tokens)

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.

Input parameters:

- `domain` (string, required): Target domain name or root URL to generate manifests for (e.g., "example.com" or "https://example.com").

### `extract_byte0_markdown` (~160 tokens)

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.

Input parameters:

- `url` (string, required): Fully qualified URL of the web page to convert into Byte-0 Markdown (e.g., "https://vercel.com/pricing").

### `query_truncation_benchmark` (~202 tokens)

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.

Input parameters:

- `domain` (string): 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.

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/quitegoodproject-answerrail-mcp/answerrail-mcp#diagnostics

## Score history

- 2026-11-04: 71
- 2026-11-03: 71
- 2026-11-02: 70
- 2026-11-01: 70
- 2026-10-31: 70
- 2026-10-30: 69
- 2026-10-29: 69

## Common questions

### What is the AnswerRail AEO, Schema.org & /llms.txt Audit MCP server?

AnswerRail AEO, Schema.org & /llms.txt Audit MCP is listed in the public MCP registry as io.github.quitegoodproject/answerrail-mcp. 6-category AI readiness, Schema.org, robots.txt, /llms.txt & 25k-token audit + auto-fix MCP server. This page covers its npm package (answerrail-mcp).

### Is the AnswerRail AEO, Schema.org & /llms.txt Audit MCP server safe to use?

AnswerRail AEO, Schema.org & /llms.txt Audit MCP scores 71 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 4 November 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the AnswerRail AEO, Schema.org & /llms.txt Audit MCP server expose?

AnswerRail AEO, Schema.org & /llms.txt Audit MCP exposes 5 tools: audit_local_codebase_and_generate, audit_ai_readiness, generate_ai_manifests, extract_byte0_markdown, query_truncation_benchmark. Their descriptions and schemas cost roughly 880 tokens of context every time the server is loaded.

### Is the AnswerRail AEO, Schema.org & /llms.txt Audit MCP server still maintained?

AnswerRail AEO, Schema.org & /llms.txt Audit MCP is still listed as active in the MCP registry. We last reached this channel on 4 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the AnswerRail AEO, Schema.org & /llms.txt Audit MCP server under?

AnswerRail AEO, Schema.org & /llms.txt Audit MCP declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- npm package: https://www.npmjs.com/package/answerrail-mcp
- Socket report: https://socket.dev/npm/package/answerrail-mcp
- Repository: https://github.com/quitegoodproject/answerrail-mcp
- Website: https://answerrail.com/
- Changelog RSS feed: https://verifymcp.io/servers/quitegoodproject-answerrail-mcp/answerrail-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/quitegoodproject-answerrail-mcp/answerrail-mcp.json
- HTML version of this page: https://verifymcp.io/servers/quitegoodproject-answerrail-mcp/answerrail-mcp