What is Docs Fetch Mcp

docs-fetch-mcp is a Model Context Protocol (MCP) server designed for fetching web page content with recursive exploration capabilities, allowing LLMs to autonomously learn about specific topics by exploring web pages and documentation.

Use cases

Use cases include enabling LLMs to gather information for academic research, exploring documentation for software development, aggregating content for knowledge bases, and assisting users in learning about specific topics through web exploration.

How to use

To use docs-fetch-mcp, you can call the fetch_doc_content tool, providing a URL of the web page you wish to fetch and an optional depth parameter to specify how many levels of linked pages to explore.

Key features

Key features include content extraction that removes distractions, link analysis for relevance, recursive exploration of linked pages, parallel processing for efficiency, robust error handling, a dual-strategy approach for fetching content, timeout prevention, and the ability to return partial results.

Where to use

docs-fetch-mcp can be used in various fields such as education, research, content aggregation, and any domain where in-depth exploration of web content is required.

Docs Fetch MCP Server

A Model Context Protocol (MCP) server for fetching web content with recursive exploration capabilities. This server enables LLMs to autonomously explore web pages and documentation to learn about specific topics.

Overview

The Docs Fetch MCP Server provides a simple but powerful way for LLMs to retrieve and explore web content. It enables:

• Fetching clean, readable content from any web page
• Recursive exploration of linked pages up to a specified depth
• Same-domain link traversal to gather comprehensive information
• Smart filtering of navigation links to focus on content-rich pages

This tool is particularly useful when users want an LLM to learn about a specific topic by exploring documentation or web content.

Features

• Content Extraction: Cleanly extracts the main content from web pages, removing distractions like navigation, ads, and irrelevant elements
• Link Analysis: Identifies and extracts links from the page, assessing their relevance
• Recursive Exploration: Follows links to related content within the same domain, up to a specified depth
• Parallel Processing: Efficiently crawls content with concurrent requests and proper error handling
• Robust Error Handling: Gracefully handles network issues, timeouts, and malformed pages
• Dual-Strategy Approach: Uses fast axios requests first with puppeteer as a fallback for more complex pages
• Timeout Prevention: Implements global timeout handling to ensure reliable operation within MCP time limits
• Partial Results: Returns available content even when some pages fail to load completely

Usage

The server exposes a single MCP tool:

fetch_doc_content

Fetches web page content with the ability to explore linked pages up to a specified depth.

Parameters:

• url (string, required): URL of the web page to fetch
• depth (number, optional, default: 1): Maximum depth of directory/link exploration (1-5)

Returns:

Installation

1. Clone this repository:

git clone https://github.com/wolfyy970/docs-fetch-mcp.git
cd docs-fetch-mcp

2. Install dependencies:

npm install

3. Build the project:

npm run build

4. Configure your MCP settings in your Claude Client:

{
  "mcpServers": {
    "docs-fetch": {
      "command": "node",
      "args": [
        "/path/to/docs-fetch-mcp/build/index.js"
      ],
      "env": {
        "MCP_TRANSPORT": "pipe"
      }
    }
  }
}

Dependencies

• @modelcontextprotocol/sdk: MCP server SDK
• puppeteer: Headless browser for web page interaction
• axios: HTTP client for making requests

Development

To run the server in development mode:

npm run dev

License

MIT