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Multi Fetch MCP Server

Multi Fetch MCP Server

Local
github.com/alexyangjieBrowser Automation1Updated 61w ago

About Multi Fetch MCP Server

Multi Fetch MCP Server is based on Anthropic's Fetch MCP Server and uses Firecrawl to retrieve web pages and convert HTML to Markdown for LLMs. It suits workflows that need concurrent URL fetching or chunked reading of long pages.

Key features

  1. 01Fetch pages and extract Markdown
  2. 02Fetch multiple URLs concurrently
  3. 03Read content from a start index
  4. 04Return raw page content
  5. 05Search and scrape results with Firecrawl

Use cases

  1. 01Retrieve web content for LLM processing
  2. 02Collect several web pages concurrently
  3. 03Read long pages in chunks
  4. 04Search the web and extract result content

MCP support

The server exposes page fetching, concurrent multi-URL fetching, and Firecrawl search tools to MCP clients, along with fetch and search prompts.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"multi-fetch": {
"command": "uvx",
"args": [
"mcp-server-multi-fetch"
],
"env": {
"FIRECRAWL_API_KEY": "<FIRECRAWL_API_KEY>",
"FIRECRAWL_API_URL": "<FIRECRAWL_API_URL>"
}
}
}
}
Run commanduvx mcp-server-multi-fetch
Environment variables to set
FIRECRAWL_API_KEYSecret
FIRECRAWL_API_URL

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypimcp-server-multi-fetch

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Multi Fetch MCP Server

This project is based on the Fetch MCP Server by Anthropic. This fork replaces direct HTTP fetching with the Firecrawl Python SDK. Set up your Firecrawl API key to enable web scraping via Firecrawl.

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: 50000)
    • start_index (integer, optional): Start content from this character index (default: 0)
    • raw (boolean, optional): Get raw content without markdown conversion (default: false)
  • fetch_multi - Fetches multiple URLs concurrently and returns an array of results. Input is an array of objects, each with:

    • url (string, required): URL to fetch
    • max_length (integer, optional): Maximum number of characters to return (default: 50000)
    • start_index (integer, optional): Start content from this character index (default: 0)
    • raw (boolean, optional): Get raw content without markdown conversion (default: false)
  • search - Searches the web using the Firecrawl search API and scrapes results in markdown and link formats by default.

    • query (string, required): Search query string
    • limit (integer, optional): Maximum number of results to return (default: 10)
Prompts
  • fetch

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

    • Search the web using the Firecrawl search API
    • Arguments:
      • query (string, required): Search query string
      • limit (integer, optional): Maximum number of results to return (default: 10)

Installation

Install the Firecrawl SDK and configure your API key before running the server:

# Install the MCP server and Firecrawl SDK
pip install mcp-server-multi-fetch firecrawl-py

# Set your Firecrawl API key (required)
export FIRECRAWL_API_KEY="fc-YOUR_API_KEY"

# Optionally, override the Firecrawl API endpoint via env or CLI
export FIRECRAWL_API_URL="https://api.firecrawl.dev"
# or
mcp-server-multi-fetch --api-url https://api.firecrawl.dev

Optionally: Install node.js, this will cause the fetch server to use a different HTML simplifier that is more robust.

Using uv (recommended)

When using uv no specific installation is needed. We will use uvx to directly run mcp-server-multi-fetch.

Configuration

Configure for Claude.app

Add to your Claude settings:

Using uvx
"mcpServers": {
  "fetch": {
    "command": "uvx",
    "args": ["mcp-server-multi-fetch"]
  }
}
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 args list in the configuration.

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

ModelContextProtocol/1.0 (Autonomous; +https://github.com/modelcontextprotocol/servers)

or

ModelContextProtocol/1.0 (User-Specified; +https://github.com/modelcontextprotocol/servers)

This can be customized by adding the argument --user-agent=YourUserAgent to the args list in the configuration.

Customization - Proxy

The server supports HTTP(S) and SOCKS5 proxies via the --proxy-url argument. For example:

# HTTP proxy
mcp-server-multi-fetch --proxy-url http://192.168.1.1:8080

# SOCKS5 proxy
mcp-server-multi-fetch --proxy-url socks5://192.168.1.1:8080

Proxy handling is provided by the Firecrawl Python SDK, which supports HTTP(S) and SOCKS5 proxies configured via the --proxy-url flag.

Customization - Firecrawl API URL

The SDK endpoint can be overridden without environment variables using --api-url:

mcp-server-multi-fetch --api-url https://api.firecrawl.dev

Debugging

You can use the MCP inspector to debug the server. For uvx installations:

npx @modelcontextprotocol/inspector uvx mcp-server-multi-fetch

Or if you've installed the package in a specific directory or are developing on it:

cd path/to/servers/src/fetch
npx @modelcontextprotocol/inspector uv run mcp-server-multi-fetch

License

mcp-server-multi-fetch is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.