Extract AI agent documentation from any website

Open-source tool to extract AI agent documentation from websites, featuring llms.txt support, MCP server, REST API, and multi-format export.

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Extract AI Agent Documentation from Any Website

This open-source tool provides a streamlined method for extracting AI agent documentation directly from any website. Designed for developers working with AI agents and LLMs, it automates the process of gathering crucial information, making it easier to understand, integrate, and build upon existing AI agent frameworks. The tool leverages advanced techniques to parse web content and identify relevant documentation, supporting various formats and integrations.

What it Does

The primary function of this tool is to scrape and extract AI agent documentation from specified URLs. It can identify and consolidate information related to Large Language Models (LLMs), including their configurations, APIs, and usage examples, often found in files named llms.txt or similar. The extracted data is then processed and made available for further use, simplifying the research and development cycle for AI builders.

Key Features

LLMs.txt Support: Specifically designed to parse and extract information from llms.txt files, a common format for documenting LLM configurations.
MCP Server Integration: Compatible with MCP servers, allowing for seamless integration into existing AI agent development environments.
REST API: Offers a REST API for programmatic access, enabling developers to automate documentation extraction within their workflows.
Multi-Format Export: Supports exporting extracted documentation in various formats, providing flexibility for different use cases and downstream processing.
Open-Source: Freely available and modifiable, fostering community contribution and transparency.

Who it's For

This tool is essential for AI developers , ML engineers , and researchers who frequently work with AI agents and LLMs. It is particularly useful for those who need to quickly gather information about existing AI agent implementations, understand their underlying LLM configurations, or integrate third-party AI agent documentation into their projects. Developers building on or interacting with MCP servers will find this tool invaluable for streamlining their documentation management.