AI Readiness

check_ai_readiness

Analyzes a website's AI search engine visibility—robots.txt, structured data, meta tags, sitemap, llms.txt—and returns a readiness score with targeted fixes for each gap.

Instructions

Check whether a website is visible to AI search engines (ChatGPT, Perplexity, Claude, Google AI Overviews). Fetches the site + robots.txt and scores AI-crawler access, structured data (JSON-LD), title/meta, Open Graph, sitemap, and llms.txt. Returns a 0-100 score, a letter grade, and a specific fix for each gap.

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_readiness"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	The website to check, e.g. example.com or https://example.com

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 13, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations provided, the description fully explains the tool's behavior: fetching the site and robots.txt, scoring multiple factors, and returning a score, grade, and specific fixes. It covers the core actions and outputs without ambiguity.

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 three sentences, front-loaded with the main action, and contains no filler. Each sentence adds essential information: purpose, process, and output.

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?

Given the moderate complexity, one required parameter, and no output schema, the description adequately explains the return value (score, grade, fix). It mentions all key components checked, making it complete for an agent to understand what the tool does.

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?

The single parameter 'url' is fully described in the schema (100% coverage). The tool description repeats the same example format, adding no new semantics 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?

The description clearly states the tool's purpose: 'Check whether a website is visible to AI search engines' and details the specific checks (robots.txt, JSON-LD, etc.). It distinguishes from the sibling tool 'generate_ai_readiness_fixes' which focuses on providing fixes.

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 does not explicitly state when to use this tool versus the sibling or alternatives. While the action is clear, there is no guidance on context or prerequisites (e.g., website must be accessible).

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

Deploy Server