Audit whether an AI agent can read a site: llms.txt, robots AI rules, structured data.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Agent Accessibility Auditor.
audit_agent_accessibilityDomain in, whether an AI agent can read that site out.
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.
Get an Apify token at console.apify.com/account/integrations.
audit_agent_accessibilityDomain 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. |
checks | array | no | Run only these checks: llms_txt, robots_ai, sitemap, openapi, security_txt, feeds, json_ld, microdata, open_graph, canonical, render_mode. Omit for all of them. A check you did not run reports null, never false, and the score is rescaled over what you selected. |
check_endpoints | boolean | no | Alias for the checks array: false removes sitemap, openapi, security_txt and feeds. Ignored when checks is set. Default true. |
check_structured_data | boolean | no | Alias for the checks array: false removes json_ld, microdata, open_graph and canonical. Ignored when checks is set. 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. |
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.
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.
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.
The actor is on the Apify Store. This wrapper is MIT licensed.
Built by Mamba Labs
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