Website Auditor MCP

Generate JSON-LD schema

generate_schema

Read-only

Generate ready-to-paste JSON-LD structured data for any domain to improve AI and search engine understanding. Supports Organization, LocalBusiness, Product, FAQPage, or auto-detect.

Instructions

Generate ready-to-paste structured data (JSON-LD schema) tailored to a website, to improve how AI assistants and search engines understand it. Use this when someone asks for "schema," "structured data," "JSON-LD," or wants the actual markup to implement a recommendation. Returns valid JSON-LD. Requires a Website Auditor subscription ($10/month; eligible new customers get a 7-day free trial — payment method required, no charge until the trial ends) — if the user doesn't have one, call get_sample_audit first to show them the exact output format, free and with no API key.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`type`	No	Schema type, or auto-detect.
`domain`	Yes	The website domain, e.g. "example.com".

Output Schema

TableJSON Schema

Name	Required	Description	Default
`jsonld`	No	The JSON-LD document, ready to paste into the site.
`placement_notes`	Yes	Where to put the snippet, e.g. "in the <head> of every page".

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.0.23Sep 9, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "jsonld": {
+      "description": "The JSON-LD document, ready to paste into the site."
+    },
+    "placement_notes": {
+      "description": "Where to put the snippet, e.g. \"in the <head> of every page\".",
+      "type": "string"
+    }
+  },
+  "required": [
+    "placement_notes"
+  ],
+  "type": "object"
+}

First observedv1.0.6Jul 29, 2026

TDQS

A4.4/5.0

Behavior4/5

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

The annotations already cover non-destructive read-only behavior. The description goes beyond them by disclosing the paid subscription requirement, the free-trial terms, and that the tool returns valid JSON-LD. It doesn't contradict the annotations and adds the non-obvious prerequisite.

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?

The description is front-loaded with the core purpose and trigger phrases, then gives return expectations and the subscription/fallback context. It is a bit longer than strictly necessary because of the trial payment details, but each sentence earns its place.

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?

Given only two parameters, an output schema, and annotations covering safety, the description covers the required context: what it does, when to use it, what it returns, and what to do if the user isn't subscribed. Nothing critical is missing for correct tool selection.

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 input schema already documents both parameters with descriptions, including the enum options and a domain example, so schema coverage is 100%. The description doesn't add parameter-specific meaning beyond what the schema provides, which lands it at the baseline.

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 states a specific verb and resource: it generates ready-to-paste JSON-LD structured data tailored to a website. It also names the exact user triggers ('schema,' 'structured data,' 'JSON-LD') and distinguishes this tool from audit/report siblings.

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

Usage Guidelines5/5

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

It explicitly says when to use the tool ('when someone asks for...') and provides a clear alternative path: if the user lacks a paid subscription, call get_sample_audit first. This is direct, actionable routing guidance.

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

Deploy Server