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Cited Geo Guide MCP Server

Developer ToolsLow Risk10.0MCP RegistryRemote
Free

Server data from the Official MCP Registry

Scan any domain for AI readiness and generate llms.txt, robots.txt and schema. Free, read-only.

About

Scan any domain for AI readiness and generate llms.txt, robots.txt and schema. Free, read-only.

Remote endpoints: streamable-http: https://getcitehound.com/api/mcp

Security Report

10.0
Low Risk10.0Low Risk

Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

13 tools verified · Open access · No issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Found in Source Code

Found by scanning the linked source code. This listing connects to a hosted endpoint, so none of this runs on your machine: it describes what the server software does where it is hosted.

file_system

Applies to the server that hosts this plugin, not to your machine.

env_vars

Applies to the server that hosts this plugin, not to your machine.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "io-github-andacuzel-citehound": {
      "url": "https://getcitehound.com/api/mcp"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

cited-geo-guide

This repository holds Citehound, an end-to-end service for AI readiness: a free scanner, Pro site reports, Fix (we make the technical changes) and Beyond (we write the content). The repository and the Vercel project keep their original names; see docs/rename-notes.md.

Benchmark data

The homepage benchmark section (and the "average of N sites" line on every scan report) is generated, not hand-written. To add a category:

  1. Scan it: node scripts/scan-category.js domains/<category>.txt <category> — writes data/<category>-raw.json (per-domain results — gitignored, never published) and data/<category>-summary.json (aggregate stats only, no company names).
  2. Add one entry to data/benchmarks.json: category (matches the summary filename), label (display name), track ("B2B SaaS" or "Consumer & e-commerce"), note (the unit word for the sample size, e.g. "platforms").
  3. Run node scripts/generate-benchmarks.js — rewrites the block in index.html between the BENCHMARKS:START/BENCHMARKS:END markers. Safe to re-run; it replaces the block in place.
  4. Commit data/benchmarks.json, the new data/<category>-summary.json, and the regenerated index.html. Leave -raw.json uncommitted — it's gitignored on purpose.

No score or count is ever typed by hand into benchmarks.json or index.html — both are read from the summary file at generation time, so they can't drift apart. Two minutes, no HTML editing.

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