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Glama

flycrawl_extract

Extract structured, typed JSON data from web pages by providing a prompt or JSON schema. Turn unstructured web content into reliable data for your applications and AI agents.

Instructions

Extracts structured, typed JSON data from web pages based on a prompt or schema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesList of URLs to extract information from.
promptNoDescription of what to extract.
schemaNoOptional JSON Schema definition for the extraction.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It briefly notes that output is 'typed JSON data' but does not mention whether the tool renders pages, handles dynamic content, requires authentication, or behaves in any other way beyond extraction.

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?

The description is a single focused sentence with no redundant or speculative content. It uses front-loaded phrasing and every word serves a purpose, making it easy for an agent to parse quickly.

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 three-parameter tool with 100% schema coverage, the description is adequate for basic invocation. However, it lacks usage context, behavioral details, and a clear distinction from sibling tools, leaving some gaps in the full picture an agent would need for confident 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 provides descriptions for all three parameters, so the baseline is 3. The description adds a small clarifying point that extraction is 'based on a prompt or schema,' which helps understand the relationship between the two optional parameters, but no additional semantics are provided.

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?

The description uses a specific verb ('Extracts') and clearly identifies the resource ('web pages') and output ('structured, typed JSON data'). It conveys the tool's core purpose effectively, though it does not explicitly mention or differentiate from sibling tools like flycrawl_scrape.

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?

No guidance is provided on when to use flycrawl_extract versus flycrawl_scrape, flycrawl_search, or flycrawl_map. The description only states what the tool does, leaving the agent to infer selection criteria from the tool name and sibling list.

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