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Check AI bot access

check_ai_bot_access
Read-onlyIdempotent

Free, instant: does a website let AI crawlers in? Checks robots.txt rules for 16 AI and search crawlers (OAI-SearchBot, GPTBot, ChatGPT-User, PerplexityBot, Claude-SearchBot, ClaudeBot, Googlebot, Google-Extended, Bingbot, Applebot, CCBot…), Cloudflare content signals, noindex/nosnippet, and whether requests identifying as AI crawlers get blocked. Also shows which product facts are readable without JavaScript.

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_ai_bot_access"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesAny page on the site, ideally a product page.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish readOnly/openWorld/idempotent/no-destructive, so the description's job is to characterize the response. It does: it discloses that results include per-crawler robots.txt evaluation, Cloudflare content signals, noindex/nosnippet, crawler-identity blocking, and which product facts are readable without JavaScript. It adds no explicit note on failure modes (unreachable site, missing robots.txt), which keeps it short of a 5.

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?

Two sentences, front-loaded with the value proposition and scope, then the detail list. The crawler enumeration is long but each name is functional signal about coverage. No filler or restated boilerplate.

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?

With no output schema, the description carries the burden of describing what comes back, and the enumerated check categories largely do that for a read-only inspection tool. It stops short of telling the agent the response shape (per-crawler allow/deny verdicts) or how long a check takes, minor but real gaps.

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?

Only one parameter, and its schema description already supplies the full guidance ('Any page on the site, ideally a product page'), so coverage is 100%. The description adds no additional meaning about the url parameter — no format, no scheme requirements, no redirect handling — so the high-coverage baseline of 3 applies.

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 ('checks whether a website lets AI crawlers in') and enumerates exactly what is inspected: robots.txt rules for 16 named crawlers, Cloudflare content signals, noindex/nosnippet, and AI-request blocking. No sibling tool does this, and the enumeration makes the scope unmistakable.

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 'Free, instant' opener implies a quick pre-check use case, which is meaningful guidance, but the description never names an alternative or an exclusion (e.g. when to use check_product_page or test_ai_shortlist instead). Usage is inferable rather than stated.

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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