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AX Audit MCP Server

Scan site for AI-agent readiness

scan_site

Run an AX Audit on a URL — scores how ready a website is for AI agents across every real AR-* check this engine runs (robots.txt AI policy, llms.txt, agent.json, JSON-LD, OpenAPI, MCP/OAuth discovery, AR-PROV provisioning, and more — the exact check count grows over time, so it is intentionally not pinned here). Returns a 0-100 score, a letter grade, and a per-check breakdown. No authentication required.

Input Schema

NameRequiredDescriptionDefault
urlYesURL to scan, e.g. https://example.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose useful behavior: no authentication is required, scans public URL readiness, returns a score, grade, and per-check breakdown, and the check count may change over time. It does not mention rate limits, timeouts, or explicitly confirm read-only behavior, but the scan semantics are otherwise well conveyed.

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?

It is front-loaded with the core action and then explains output and the dynamic check count. The long parenthetical checklist is useful but somewhat overstuffed, keeping it short of a perfect score.

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?

For a one-parameter scanner with no output schema, the description is mostly complete: it explains the return shape, that no auth is needed, and that check coverage evolves. It omits sibling differentiation and any operational limits, but those are secondary for this simple tool.

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?

There is a single URL parameter with 100% schema description coverage, so the schema already documents its meaning. The description only says the audit runs on a URL, not adding format or validation details beyond the schema.

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?

States a specific verb and resource: run an AX Audit on a URL, with scope covering AI-agent readiness checks and return values. It is clear what the tool does, but it never distinguishes itself from the sibling run_full_audit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

Provides no explicit guidance on when to use scan_site versus run_full_audit, nor any when-not conditions. The context implies this is a URL readiness scan, but the agent is left to infer the choice between siblings.

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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