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Docs Fetch MCP Server: Recursive Crawling & Seamless Data Extraction - MCP Implementation

Docs Fetch MCP Server: Recursive Crawling & Seamless Data Extraction

Docs Fetch MCP Server: Powerful web content retrieval with recursive crawling, efficiently exploring complex sites for seamless data extraction.

Research And Data
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80% of users reported increased productivity after just one week

About Docs Fetch MCP Server

What is Docs Fetch MCP Server: Recursive Crawling & Seamless Data Extraction?

Docs Fetch MCP Server is a purpose-built tool enabling Large Language Models (LLMs) to autonomously explore and learn from web documentation. By combining recursive hyperlink traversal with intelligent content distillation, it empowers developers to extract structured knowledge from websites while avoiding navigational noise. This MCP server acts as a smart intermediary between LLMs and the web, ensuring focused, error-resilient data gathering.

How to Use Docs Fetch MCP Server: Recursive Crawling & Seamless Data Extraction?

Interact with the server through its core fetch_doc_content tool:

  • Specify the starting URL and optional exploration depth (1-5)
  • Receive structured output containing main content, linked pages, and metadata
  • Automatically handles parallel requests and fallback strategies for complex pages

Integration requires configuring the MCP server path and environment variables as shown in the installation guide.

Docs Fetch MCP Server Features

Key Features of Docs Fetch MCP Server: Recursive Crawling & Seamless Data Extraction?

Stand out with these advanced capabilities:

  • Context-Aware Crawling: Prioritizes content-rich pages while ignoring redundant navigation elements
  • Adaptive Fetching: Uses lightweight HTTP requests first, with headless browser fallback for JavaScript-heavy sites
  • Depth Control: Granular exploration limits to prevent unnecessary resource consumption
  • Error Mitigation: Built-in retries and partial results delivery ensure robust operation under unstable conditions

Use Cases for Docs Fetch MCP Server: Recursive Crawling & Seamless Data Extraction?

Ideal scenarios include:

  • Automated documentation indexing for developer tools
  • Systematic research data collection from technical websites
  • LLM training data preparation from structured web sources
  • Continuous monitoring of API reference updates

Docs Fetch MCP Server FAQ

FAQs About Docs Fetch MCP Server: Recursive Crawling & Seamless Data Extraction?

  • How does depth work? Each level explores links one step further from the starting page
  • Can it handle login-protected pages? Requires configuring authentication headers in client requests
  • What formats are supported? Automatically parses HTML, Markdown, and JSON-based documentation
  • How to monitor progress? Built-in logging shows request status and content extraction metrics

Content

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:

{
  "rootUrl": "https://example.com/docs",
  "explorationDepth": 2,
  "pagesExplored": 5,
  "content": [
    {
      "url": "https://example.com/docs",
      "title": "Documentation",
      "content": "Main page content...",
      "links": [
        {
          "url": "https://example.com/docs/topic1",
          "text": "Topic 1"
        },
        ...
      ]
    },
    ...
  ]
}

Installation

  1. Clone this repository:
git clone https://github.com/wolfyy970/docs-fetch-mcp.git
cd docs-fetch-mcp
  1. Install dependencies:
npm install
  1. Build the project:
npm run build
  1. 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

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