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extract_data

Extracts structured data (JSON-LD, OpenGraph, meta tags) and trust scores from any URL, providing reliable facts like prices and products.

Instructions

Extract the structured data a page already declares — JSON-LD (schema.org), OpenGraph cards, and meta tags — plus the AIO trust score. Deterministic, no AI: returns only data present in the page. Use for fast, reliable facts (prices, products, articles) when the site publishes structured data.

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": "extract_data"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	The URL to extract structured data from.
`fresh`	No	If true, bypass cache and fetch fresh content. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.5.0Aug 5, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key traits: deterministic ('no AI'), scoped to existing data ('only data present in the page'), and lists data types extracted. It does not mention caching behavior or error handling, which prevents a 5.

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?

Two sentences: the first front-loads the core function with specific data types, the second provides the use case and deterministic guarantee. No fluff or redundant language.

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?

The tool is simple with 2 parameters and no output schema. The description covers input, output scope, and deterministic behavior. It could mention the return structure or caching effects, but overall it is adequate for an agent to select and invoke the tool correctly.

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 coverage is 100% for both parameters (url and fresh), so the schema fully documents them. The description adds no additional parameter semantics beyond the schema, earning the baseline score of 3.

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 uses the specific verb 'extract' and names the resource: structured data a page already declares (JSON-LD, OpenGraph, meta tags) plus the AIO trust score. It distinguishes itself from sibling tools like read_url or score_url by focusing on structured data extraction and deterministic behavior.

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?

The description explicitly states when to use this tool: 'Use for fast, reliable facts (prices, products, articles) when the site publishes structured data.' This implies when not to use, but it does not name alternative tools or exclusions, so it falls short of a 5.

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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