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    Mcp Fetch Node

    A Model Context Protocol server that provides web content fetching capabilities.

    7 stars
    TypeScript
    Updated Jun 12, 2025
    fetch
    mcp
    mcp-server

    Table of Contents

    • Description
    • Available Tools
    • Available Prompts
    • Usage
    • Customization - robots.txt
    • Customization - User-agent
    • Key differences with the original project
    • Features
    • Development
    • Contributing
    • License
    • TODO

    Table of Contents

    • Description
    • Available Tools
    • Available Prompts
    • Usage
    • Customization - robots.txt
    • Customization - User-agent
    • Key differences with the original project
    • Features
    • Development
    • Contributing
    • License
    • TODO

    Documentation

    Fetch MCP Server

    A port of the official Fetch MCP Server for Node.js. Please check the key differences with original project section for more details.

    Description

    A Model Context Protocol server that provides web content fetching capabilities. This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.

    The fetch tool will truncate the response, but by using the start_index argument, you can specify where to start the content extraction. This lets models read a webpage in chunks, until they find the information they need.

    Available Tools

    • fetch - Fetches a URL from the internet and extracts its contents as markdown.
    • url (string, required): URL to fetch
    • max_length (integer, optional): Maximum number of characters to return (default: 5000)
    • start_index (integer, optional): Start content from this character index (default: 0)
    • raw (boolean, optional): Get raw content without markdown conversion (default: false)

    Available Prompts

    • fetch - Fetch a URL and extract its contents as markdown
    • url (string, required): URL to fetch

    Usage

    mcp-fetch-node exposes an SSE endpoint at /sse on port 8080 by default.

    Node.js:

    bash
    npx -y mcp-fetch-node

    Docker:

    bash
    docker run -it tgambet/mcp-fetch-node

    Customization - robots.txt

    By default, the server will obey a websites robots.txt file if the request came from the model (via a tool), but not if the request was user initiated (via a prompt). This can be disabled by adding the argument --ignore-robots-txt to the run command.

    Customization - User-agent

    By default, depending on if the request came from the model (via a tool), or was user initiated (via a prompt), the server will use either the user-agent

    code
    # Tool call
    ModelContextProtocol/1.0 (Autonomous; +https://github.com/tgambet/mcp-fetch-node)
    
    # Prompt
    ModelContextProtocol/1.0 (User-Specified; +https://github.com/tgambet/mcp-fetch-node)

    This can be customized by adding the argument --user-agent=YourUserAgent to the run command, which will override both.

    Key differences with the original project

    • This implementation is written in TypeScript and targets the Node.js runtime.

    It is suited for situations where python is not available.

    • This implementation provides an SSE interface instead of stdio.

    It is more suitable for deployment as a web service, increasing flexibility.

    • This implementation does not rely on Readability.js library for content extraction.

    It uses a custom implementation that is more generic and suited for websites other that news-related ones.

    The api and tool description is, however, the same as the original project so you can try mcp-fetch-node as a drop-in replacement for the original project.

    Please report any issue to the issue tracker.

    Features

    • Fetch and extract relevant content from a URL
    • Respect robots.txt (can be disabled)
    • User-Agent customization
    • Markdown conversion
    • Pagination

    Development

    bash
    pnpm install
    pnpm dev
    pnpm lint:fix
    pnpm format
    pnpm test
    pnpm build
    pnpm start
    pnpm inspect

    Contributing

    Contributions are welcome! Please feel free to submit a Pull Request.

    License

    MIT

    TODO

    • [ ] Add user logs and progress
    • [ ] Add documentation & examples
    • [ ] Performance benchmarks and improvements
    • [ ] Benchmarks for extraction quality: cf https://github.com/adbar/trafilatura/blob/master/tests/comparison_small.py

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