AnswerRail AEO, Schema.org & /llms.txt Audit MCP
NPM · ANSWERRAIL-MCP · 2 COMPONENTS
6-category AI readiness, Schema.org, robots.txt, /llms.txt & 25k-token audit + auto-fix MCP server
Available components
Last scanned (21 hours ago)
Scores higher than 40% of npm servers
Category Web Scraping
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. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 3 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability82
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (good).Pass
- 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. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management20
- Stability observed for 6 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities20
- Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28. See how to fix → Fail
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 3 Nov 26 +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.
- 31 Oct 26 +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.
- 29 Oct 26 69
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 4 Nov 2026 · Analysed npm/answerrail-mcp@1.2.7
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Dependencies 0 packages
| Packages resolved | 0 |
|---|---|
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
audit_ai_readiness Audit Website AI Crawler & Lighthouse 13.5 Readiness ~201
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.
| Name | Type | Req | Description |
|---|---|---|---|
| url | string | yes | 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. |
No output schema declared.
No examples provided.
audit_local_codebase_and_generate Audit Local Codebase (20+ Schema.org & 14+ AI Bot Rules) & Generate /llms.txt + ai-catalog.json ~170
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.
| Name | Type | Req | Description |
|---|---|---|---|
| outputAll | boolean | – | When true (default), actively writes compliant /llms.txt and /.well-known/ai-catalog.json into public/ or targetDir. |
| targetDir | string | yes | Local project directory path to scan and write manifests into (e.g., "./" or "."). |
No output schema declared.
No examples provided.
extract_byte0_markdown Extract Clean Byte-0 Markdown & Schema Tables from URL ~160
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.
| Name | Type | Req | Description |
|---|---|---|---|
| url | string | yes | Fully qualified URL of the web page to convert into Byte-0 Markdown (e.g., "https://vercel.com/pricing"). |
No output schema declared.
No examples provided.
generate_ai_manifests Generate /llms.txt & Lighthouse 13.5 ai-catalog.json Manifests ~147
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.
| Name | Type | Req | Description |
|---|---|---|---|
| domain | string | yes | Target domain name or root URL to generate manifests for (e.g., "example.com" or "https://example.com"). |
No output schema declared.
No examples provided.
query_truncation_benchmark Query 2026 50-Site SaaS AI Truncation & /llms.txt Benchmark ~202
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.
| Name | Type | Req | Description |
|---|---|---|---|
| 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. |
No output schema declared.
No examples provided.
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.
npm · answerrail-mcp
claude mcp add quitegoodproject-answerrail-mcp -- npx -y answerrail-mcp
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.