Skip to main content
Glama

extract

Fetch any webpage and use AI to extract specific structured data such as pricing, specs, or contact info based on your prompt.

Instructions

Fetch a webpage and extract specific information using AI. Use this when you need structured data from a page (e.g. pricing, specs, contact info) rather than the raw content. Costs 5 credits.

Returns: content (the extracted text), url, credits_used, credits_remaining, usage (token counts).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to extract from
promptYesWhat information to extract (e.g. "list all pricing tiers with features" or "extract the author name and publication date")
Behavior3/5

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

No annotations, so description carries full burden. Mentions cost (5 credits) and return fields, indicating it's a read operation. Does not detail error cases, rate limits, or behavior on malformed URLs.

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 compact sentences plus a return field list. Front-loaded with purpose. Every sentence adds value without redundancy.

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 simple 2-param tool with clear description, it sufficiently covers purpose, usage, and output. Lacks error handling or edge case details, but overall complete for typical use.

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 100%, so parameters are already well-described in schema. Description adds credit cost and return fields but no new parameter-level detail beyond what schema provides.

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?

Describes fetching a webpage using AI to extract structured data, clearly distinguishing from raw content. Gives examples like pricing, specs, contact info. Specific verb+resource+scope.

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?

Explicitly states when to use (for structured data rather than raw content) and mentions credit cost. Suggests alternatives implicitly with sibling tools fetch and search. No explicit when-not-to-use.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sofya-co/sofya-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server