Agent Accessibility Auditor MCP Server

Agent Accessibility Auditor MCP Server

Audits a domain to determine if AI agents and crawlers can access and read it, returning a flat row of 42 fields covering llms.txt, robots.txt AI policy, structured data, render mode, and machine-readable endpoint discovery.

Category
Visit Server

README

Agent Accessibility Auditor MCP Server

Smithery Glama score MCP Registry npm version npm downloads license mcpservers.org

MCP server for the Mamba Labs Agent Accessibility Auditor actor on Apify.

Can an AI agent read this site? Give it a domain and it returns one flat row of 42 fields covering five families of fact: the llms.txt family, robots AI crawler policy including the newer Content Signal directives, structured data presence and health, render mode, and machine readable endpoint discovery.

Install

npx -y @mambalabsdev/mcp-agent-accessibility-auditor

Claude Desktop

{
  "mcpServers": {
    "mamba-agent-accessibility-auditor": {
      "command": "npx",
      "args": ["-y", "@mambalabsdev/mcp-agent-accessibility-auditor"],
      "env": { "APIFY_TOKEN": "your-apify-token" }
    }
  }
}

Get an Apify token at console.apify.com/account/integrations.

Tool

audit_agent_accessibility

Domain in, whether an AI agent can read that site out.

Input Type Required Notes
domain string yes One company domain, for example vercel.com. Protocol and path are stripped.
check_endpoints boolean no Probes sitemap, OpenAPI, well known files and feeds. Adds 7 concurrent requests. Default true.
check_structured_data boolean no Parses JSON-LD, microdata, Open Graph and canonical off the homepage. Costs no extra requests. Default true.
skipCache enum no Leave as false to use the 7 day cache. Set to true to re-audit the domain from scratch. Default false.

Reading the output

Every field is a fact read off a fetch. No model is called at any point, so the same domain returns the same row today and next month unless the site actually changed.

has_llms_txt is true only when /llms.txt returns 200 and the body is real markdown, and llms_txt_reject_reason says why a 200 was not counted. Twelve requests per domain, robots.txt first and then the homepage and ten probes concurrently. Typical wall clock is 2 to 4 seconds.

Built for a technical SEO or growth engineer preparing a site for AI crawlers and agent traffic, or an agency selling that work and needing a before and after audit across a client list.

Billing

You are charged per domain analyzed, plus a small actor start fee. A repeat run inside the 7 day cache window costs nothing new.

Pricing is on the actor's Apify page. Running this server consumes Apify credits.

What this server does and does not do

It is a thin client for the Apify actor. It passes your input through and returns the actor's output unchanged. Every behavior described above lives in the actor, not here.

Errors are surfaced, never swallowed. An invalid input, an invalid token, an exhausted balance, a timeout, or a run that returns anything other than a dataset all come back as an explicit tool error rather than as an empty result.

Source

The actor is on the Apify Store. This wrapper is MIT licensed.

Built by Mamba Labs

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured