Extract LLMs Docs

v1.0.0Knowledge & Memorystable

Extract documentation for AI agents from any site with llms.txt support. Features MCP server, REST API, batch processing, and multiple export formats.

aiai-agentsclaudecursordeveloper-tools
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What is Extract LLMs Docs?

Extract LLMs Docs is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to extract documentation for ai agents from any site with llms.txt support. features mcp server, rest api, batch processing, and multiple export formats.

Extract documentation for AI agents from any site with llms.txt support. Features MCP server, REST API, batch processing, and multiple export formats.

This server falls under the Knowledge & Memory category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • Extract documentation for AI agents from any site with llms.

Use Cases

Parse llms.txt files
Extract documentation
Support AI model training
nirholas

Maintainer

LicenseMIT
Languagetypescript
Versionv1.0.0
UpdatedMay 10, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx extract-llms-docs

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Extract LLMs Docs

Extract LLMs Docs (llm.energy) is an MCP server that lets AI assistants fetch and process developer documentation from any website that publishes an llms.txt file — the emerging standard for AI-readable site indexes. It provides tools to extract docs in clean Markdown, validate whether a site supports llms.txt, discover documentation URLs, and browse a directory of known llms.txt-enabled sites, enabling AI coding agents to pull accurate, up-to-date library documentation on demand rather than relying on training data.

Prerequisites

  • Node.js 18+ installed for running npx
  • An MCP-compatible client such as Claude Desktop, Cursor, or VS Code
  • Internet access to reach target documentation sites
  • Optional: ADMIN_KEY environment variable for cache management operations
1

Install and run via npx

The MCP server is published under @llm-energy/mcp-server and can be run directly with npx without a prior install step.

npx -y @llm-energy/mcp-server
2

Add the server to your MCP client config

Add the extract-llms-docs server to your Claude Desktop or Cursor configuration. No API keys are required for basic usage.

{
  "mcpServers": {
    "extract-llms-docs": {
      "command": "npx",
      "args": ["-y", "@llm-energy/mcp-server"]
    }
  }
}
3

Restart your MCP client

Restart Claude Desktop or your MCP client to load the new server. You should see tools like extract_docs, validate_url, and list_sites become available.

4

Validate a site's llms.txt support

Before extracting docs, use validate_url to check if a target site supports llms.txt. This quickly confirms whether full documentation extraction will work.

5

Extract documentation from a site

Use the extract_docs tool with a URL to pull clean Markdown documentation from any llms.txt-enabled site. The result is structured content ready for AI consumption.

Extract LLMs Docs Examples

Client configuration

Claude Desktop configuration for the Extract LLMs Docs MCP server.

{
  "mcpServers": {
    "extract-llms-docs": {
      "command": "npx",
      "args": ["-y", "@llm-energy/mcp-server"],
      "env": {
        "ADMIN_KEY": "optional_admin_key_for_cache_management"
      }
    }
  }
}

Prompts to try

Example prompts for extracting and searching developer documentation.

- "Check if https://docs.anthropic.com supports llms.txt"
- "Extract the documentation from https://fastapi.tiangolo.com using llms.txt"
- "Discover all documentation URLs available at https://nextjs.org"
- "List known sites that support llms.txt and filter by developer tools"
- "Search the llms.txt site directory for Python libraries"

Troubleshooting Extract LLMs Docs

extract_docs returns no content or an error for a site

First use validate_url to confirm the site supports llms.txt. If it does not, the site has not published an llms.txt file and documentation cannot be extracted with this tool.

Rate limit errors when extracting docs from multiple sites

The server enforces rate limits (default: 100 requests per 60-second window). Space out your requests or self-host the server and set RATE_LIMIT_REQUESTS and RATE_LIMIT_WINDOW_MS to higher values.

Stale documentation being returned from cache

The server caches results for CACHE_TTL seconds (default 3600). To flush the cache for a specific site, use the admin API endpoint with your ADMIN_KEY, or wait for the cache to expire.

Frequently Asked Questions about Extract LLMs Docs

What is Extract LLMs Docs?

Extract LLMs Docs is a Model Context Protocol (MCP) server that extract documentation for ai agents from any site with llms.txt support. features mcp server, rest api, batch processing, and multiple export formats. It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Extract LLMs Docs?

Follow the installation instructions on the Extract LLMs Docs GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Extract LLMs Docs?

Extract LLMs Docs works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Extract LLMs Docs free to use?

Yes, Extract LLMs Docs is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

Browse More Knowledge & Memory MCP Servers

Explore all knowledge & memory servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "extract-llms-docs": { "command": "npx", "args": ["-y", "extract-llms-docs"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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