YourAITools MCP Hub

AgentReady: AI-agent readiness audit

audit_website

Read-onlyIdempotent

AI-agent readiness audit of a website: score 0-100, grade and verdict across agent access (robots.txt rules for AI bots, bot challenges), readable content (raw HTML, markdown), discovery (llms.txt, sitemap, JSON-LD, meta/OG), agent interfaces (OpenAPI, MCP, A2A agent card, x402) and speed/HTTPS. Free preview tier: score, grade and category scores. The paid x402 endpoints /v1/lite ($0.005) and /v1/audit ($0.03) add the findings, prioritized fixes and ready-to-paste snippets (llms.txt draft, robots.txt lines, JSON-LD).

[AgentReady via YourAITools MCP Hub] Free tier: same as AgentReady's own MCP server (call without payment and without tier). Paid: lite $0.005 / audit $0.03 per call, with a credits key (Authorization: Bearer yatc_...) or x402 (USDC; the hub returns the payment terms). Failed tool calls aren't charged: credits are refunded automatically and x402 payments only settle on success.

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": "audit_website"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	Website URL or domain to audit, e.g. https://example.com or stripe.com (public http/https only)
`tier`	No	Paid tier: lite $0.005, audit $0.03. Omit tier (with no credits key or x402 payment) to use the free tier.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 30, 2026
- addedInput schema / properties / url / examples
```
Added value: +[
+  "https://example.com"
+]
```
First observedOct 24, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/openWorld, and the description adds substantial context beyond them: the two payment paths (Bearer credits key or x402 USDC), the exact price per call, and the failure policy (credits refunded, x402 settles only on success). This is precisely the operational detail an agent needs before invoking a paid, network-facing tool.

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?

Purpose and scoring dimensions are front-loaded in the first sentence, and the bracketed hub note is clearly separated. There is some duplication — lite/audit prices appear in both paragraphs and again in the schema — which costs it a point but does not bury the signal.

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

Completeness5/5

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 return-value burden and does so: it names the free-tier outputs (score, grade, category scores) and what each paid tier adds. Auth, pricing and refund behavior are all covered, so an agent can call it correctly end to end.

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?

Schema coverage is 100%, so the baseline is 3; the description earns extra by explaining what the 'tier' enum actually buys — lite/audit add findings, prioritized fixes and ready-to-paste snippets (llms.txt draft, robots.txt lines, JSON-LD) beyond the free score/grade. That is return-value meaning the schema does not carry.

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+resource ('AI-agent readiness audit of a website') and enumerates the exact dimensions scored: agent access, readable content, discovery, agent interfaces, speed/HTTPS. An agent can distinguish this from siblings like check_domain, scan_url or detect_stack without opening any schema.

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?

Gives clear tier-selection guidance: omit tier with no credits key or x402 payment to get the free preview, or pick lite/audit for findings and fixes. However, it never states when to prefer this over sibling tools such as check_mcp_server or scan_url, so the alternative-selection guidance is missing.

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

All YourAITools MCP Hub tools Inspect

Try in Browser

Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?