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ai-visibility-mcp

ai-visibility-mcp

by tsushanth
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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check_visibility

Check a website's AI-crawler accessibility by analyzing its live robots.txt for bot blocking rules and verifying the presence of an llms.txt file.

Instructions

Check a site's actual AI-crawler visibility: fetch its live robots.txt and look for Disallow rules blocking named AI bots (GPTBot, ClaudeBot, Google-Extended, PerplexityBot, etc.) or a wildcard block, plus whether llms.txt actually exists as a real file (vs. falling through to a SPA catch-all).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "check_visibility"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesSite URL or bare domain, e.g. example.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It explains the tool fetches a live resource and checks for specific bot names, which implies it's a read-only network operation. However, it doesn't disclose that it may make external requests, handle timeouts, or fail on invalid URLs. Given no annotations, the description does some work but misses key behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, well-structured, and front-loaded with the tool's purpose. It is concise but covers the main actions without unnecessary detail. It earns its place but could be slightly more efficient in phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description is reasonably complete. It explains what the tool fetches, what specific checks it performs (named bots, wildcard block, llms.txt existence), and the nuance of SPA catch-all. It doesn't explain the return format, but given the lack of an output schema, a 4 is appropriate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers the single parameter (url) 100%, and the description adds meaning by explaining the parameter is a site URL or bare domain (e.g., example.com). The description also provides typical usage context (robots.txt fetch and llms.txt check), which goes beyond the schema's basic description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks a site's AI-crawler visibility by fetching robots.txt and looking for Disallow rules for named AI bots and a wildcard block, and verifies llms.txt existence. It uses a specific verb (Check) and resource (site's AI-crawler visibility), distinguishing it from siblings like cloudflare_ai_bot_audit or generate_llms_txt.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on what the tool does (checking robots.txt and llms.txt). It doesn't explicitly state when NOT to use it or mention alternatives, but the sibling tools (cloudflare_ai_bot_audit and generate_llms_txt) imply different use cases. The description is sufficient for an agent to decide when to invoke this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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