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extract_data

Extract structured data from any webpage using JSON schema. AI-powered extraction that understands page context. Price: $0.03, up to 3x on bot-protected or complex sites

Input Schema

NameRequiredDescriptionDefault
urlYesThe URL to process
schemaYesJSON schema for extraction
instructionsNoNatural language extraction hints

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • changedInput schema / properties / instructions / example
      Previous value: -"Extract product details"New value: +"Extract the page title and what the domain is for"
    • removedInput schema / properties / schema / example / name
      Removed value: -{
-  "type": "string"
-}
    • removedInput schema / properties / schema / example / price
      Removed value: -{
-  "type": "number"
-}
    • addedInput schema / properties / schema / example / purpose
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / properties / schema / example / title
      Added value: +{
+  "type": "string"
+}
    • changedInput schema / properties / url / example
      Previous value: -"https://example.com/product"New value: +"https://example.com"
  2. Changed9 schema fields changed
    • changedInput schema / properties / instructions / description
      Previous value: -"Natural language instructions to guide extraction"New value: +"Natural language extraction hints"
    • addedInput schema / properties / instructions / example
      Added value: +"Extract product details"
    • addedInput schema / properties / schema / additionalProperties
      Added value: +{}
    • changedInput schema / properties / schema / description
      Previous value: -"JSON schema defining the data structure to extract"New value: +"JSON schema for extraction"
    • addedInput schema / properties / schema / example
      Added value: +{
+  "name": {
+    "type": "string"
+  },
+  "price": {
+    "type": "number"
+  }
+}
    • addedInput schema / properties / schema / propertyNames
      Added value: +{
+  "type": "string"
+}
    • changedInput schema / properties / url / description
      Previous value: -"The URL to extract from"New value: +"The URL to process"
    • addedInput schema / properties / url / example
      Added value: +"https://example.com/product"
    • addedInput schema / properties / url / format
      Added value: +"uri"
  3. First observed

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses cost ($0.03, up to 3x on bot-protected or complex sites) and that extraction is AI-powered with page-context understanding, but says nothing about authentication, rate limits, failure behavior, or what happens to pages it cannot render.

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?

Three tight sentences: purpose, mechanism, and cost, with the core capability front-loaded. No filler, and the pricing caveat is placed after the value proposition.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 3-parameter tool with no annotations and no output schema, the description covers purpose, mechanism, and cost but never states the return shape (structured JSON matching the supplied schema is only implied) or error behavior. Nested-object input and AI-driven extraction would benefit from a note on expected output.

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 description coverage is 100%, so url, schema, and instructions are already documented in the schema, and the description adds no syntax or format detail beyond them. Baseline 3 applies when the schema does the heavy lifting.

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 (extract) and resource (structured data from a webpage) plus the key mechanism (JSON schema), which separates it from plain fetch tools like fetch_webpage or get_contents. It never names a sibling, so the differentiation is implied rather than explicit.

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?

The description conveys the extraction scenario but gives no when-to-use routing against siblings such as fetch_webpage, get_contents, crawl_site, or extract_pdf, and no prerequisites. The price mention hints this is a metered/premium call but does not say when that cost is warranted.

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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