Skip to main content
Glama

Extract Web Page Content (Tavily)

search.ai.extract
Read-onlyIdempotent

Extract clean readable content from up to 20 URLs: text, title, author, date. Eliminates scraping. Feed web pages into AI agent context windows.

Instructions

Extract clean readable content from up to 20 URLs — returns text, title, author, published date. Eliminates scraping. Perfect for feeding web pages into agent context windows (Tavily)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesURLs to extract clean content from (1-20 URLs). Returns readable text, title, author, date.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and idempotentHint=true. The description adds valuable context: it returns specific fields (text, title, author, published date), handles up to 20 URLs, and eliminates scraping—disclosing its behavior beyond the annotations without contradiction.

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, zero wasted words. The description is front-loaded with the main action and result, then additional context. Every 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 the tool's simplicity (one parameter, output schema exists), the description covers the core purpose, return fields, use case, and constraints. It is complete enough for an agent to understand when and how to invoke it without confusion.

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% for the 'urls' parameter. The description does not add meaningful parameter-specific semantics beyond the schema's own description. It reiterates the count limit (1-20 URLs) but does not explain formatting or constraints like whether URLs must be HTTP/HTTPS. Baseline 3 is appropriate as schema does the heavy lifting.

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 clearly states the verb 'Extract' and the resource 'clean readable content from up to 20 URLs'. It specifies the returned fields (text, title, author, published date) and distinguishes itself from scraping tools by claiming 'Eliminates scraping'. This differentiates it from sibling tools like search.ai.web or scraping.spider.scrape.

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 provides a clear use case: 'Perfect for feeding web pages into agent context windows (Tavily)'. However, it does not explicitly state when not to use this tool versus alternatives (e.g., when raw HTML or links are needed). It implicitly guides usage but lacks explicit exclusions or comparisons.

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/whiteknightonhorse/APIbase'

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