Citation Intelligence MCP

audit_crawler_access

Read-onlyIdempotent

Test whether AI crawlers such as GPTBot and ClaudeBot can fetch a URL. Parse robots.txt and run live GETs per bot User-Agent to detect access blocks.

Instructions

Verify that major AI crawlers (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, CCBot, Google-Extended, Applebot-Extended, Bytespider, Meta-ExternalAgent, plus real-time fetch UAs) can fetch a URL. Parses robots.txt and does a live GET with each bot's User-Agent. Surfaces robots.txt blocks AND UA-based gating that breaks AI citation.

Input Schema

TableJSON Schema

Name	Required	Description
`url`	Yes	Page URL to test for AI crawler access.
`bots`	No	Override the default bot list. Each entry is a User-Agent token (e.g. 'GPTBot', 'ClaudeBot').
`fetch_with_ua`	No	If true, do a live GET as each bot's User-Agent and report status. Disable to only parse robots.txt (no extra requests).

Output Schema

TableJSON Schema

Name	Required	Description
`url`	Yes	The URL that was audited.
`bots`	Yes	Per-bot access verdict combining robots.txt + live UA test.
`note`	No
`summary`	Yes
`fetched_at`	Yes	UTC ISO-8601 timestamp.
`robots_url`	Yes	robots.txt URL that was parsed.
`robots_error`	Yes	Error message if robots.txt fetch failed.
`robots_status`	Yes	HTTP status of the robots.txt fetch.
`robots_present`	Yes	Whether a non-empty robots.txt was found.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.1.2Oct 2, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false. The description adds valuable behavioral context beyond that: it parses robots.txt and makes live GET requests using each bot's User-Agent, and it surfaces both robots.txt blocks and UA-based gating. It does not mention timeouts, rate limits, or network cost, but the added detail is substantial.

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

Conciseness5/5

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

Three tightly packed sentences with no filler. The core action is front-loaded, and the long crawler list is justified because those names are operationally relevant to the tool.

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?

An output schema exists, so the description need not explain return values. Annotations cover the safety profile and the description covers the core behavior, making it nearly complete. It could still be clearer about when this tool is preferable to sibling audit tools, but no critical invocation detail is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents url, bots, and fetch_with_ua. The description names the default bot list, which lightly reinforces the bots parameter, but adds no syntax or behavioral meaning beyond what the schema already provides.

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?

States a specific verb and resource: verify AI crawler access to a URL. It names the crawler set and explains that it parses robots.txt and performs live GETs, clearly distinguishing it from broader audit siblings like audit_sitemap or audit_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 Guidelines3/5

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

The description makes the use case inferable — diagnosing whether AI crawlers can fetch a page — but does not explicitly say when to choose this over sibling audit tools, nor does it state exclusions or prerequisites. Usage is implied rather than spelled out.

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