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AI Crawler Access Checker

ai-crawler-access-checker
Read-only

Check which AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended & more) can access your website. Bulk audit of robots.txt rules, llms.txt presence and sitemap for AI search visibility (GEO/AEO). — $0.01/call, x402 (USDC on base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
websitesYesList of website URLs or domains to audit (e.g. `example.com` or `https://example.com`).
maxConcurrencyNoHow many websites to check in parallel.

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds valuable behavioral context: it mentions the $0.01/call pricing and x402 payment method, which are not in annotations, and clarifies it's a bulk audit of specific files. This adds meaningful information beyond the structured fields.

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?

The description is two concise sentences that front-load the main purpose ('Check which AI crawlers...') and then add supporting details. There is no redundant fluff; every clause earns its place.

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

Completeness3/5

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

The tool is moderately complex (bulk audit of multiple sites and files), and there's no output schema. The description doesn't explain what the output looks like (e.g., a report of allowed/blocked crawlers per site) or how to interpret results. It also doesn't mention rate limits or error handling, though it does cover cost and input semantics.

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 baseline is 3. The description's mention of 'bulk audit of robots.txt rules, llms.txt presence and sitemap' gives some context for what the 'websites' parameter does, but it doesn't add per-parameter syntax or format details beyond the schema's existing descriptions.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Check which AI crawlers... can access your website,' using a specific verb and resource. It also lists the specific crawlers and what it audits, but it doesn't explicitly differentiate itself from siblings like llms-txt-auditor, which might overlap on llms.txt checks.

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 implies when to use it (for AI search visibility auditing) by mentioning robots.txt, llms.txt, and sitemap checks, but it provides no explicit exclusions or alternatives. It doesn't tell the agent when to prefer this tool over the sibling 'llms-txt-auditor' or others.

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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TDQS

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct aspect of SEO/GEO/AEO: AI answer changes, crawler access, cited sources, brand visibility, llms.txt auditing, pricing, and social previews. No two tools overlap in purpose, ensuring clear selection.

Naming Consistency4/5

Most tools use descriptive snake_case with hyphens (e.g., ai-answer-change-alert), but pricing_info breaks the pattern with an underscore. Overall, names are clear and follow a logical prefix system (ai-, llms-, social-).

Tool Count5/5

Seven tools is an ideal size for a specialized MCP server. Each tool has a clear function, and the count is neither sparse nor overwhelming.

Completeness4/5

The set covers core GEO/AEO workflows (crawler access, LLM answers, brand visibility, llms.txt) plus social previews and pricing. Minor gaps exist (e.g., no keyword or competitor analysis), but the domain is well-served.

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