MCP Fetch As Markdown MCP Server

A Model Context Protocol (MCP) server that fetches web pages and converts them to clean, readable markdown format, focusing on main content

Local serverstdioPython

What is the MCP Fetch As Markdown MCP server?

MCP Fetch As Markdown MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. A Model Context Protocol (MCP) server that fetches web pages and converts them to clean, readable markdown format, focusing on main content extraction while minimizing context overhead.

What you get

This MCP server acts as a bridge between AI assistants and the web, specifically designed to:

What the assistant can call

Once MCP Fetch As Markdown is connected, these are the calls the assistant has available:

  • Attribution — Give proper credit to original sources when using extracted content
  • Prerequisites — The Prerequisites tool exposed by this server
  • fetch — The fetch tool exposed by this server
  • Customization — The Customization tool exposed by this server
  • Debugging — Enable debug logging by modifying the logging level in main.py: python logging.basicConfig(level=logging.DEBUG)

Setting it up

git on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.

Configuration and credentials

  • Python 3.12 or higher - uv package manager

Choosing this one

Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. MCP Fetch As Markdown's toolset — Attribution, Prerequisites, fetch and 2 more — is a fair guide to whether it matches your workflow. It is maintained by bhubbb; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the mcp fetch as markdown mcp server does with a few real requests.

Available tools

ToolWhat it does
AttributionGive proper credit to original sources when using extracted content
PrerequisitesThe Prerequisites tool exposed by this server.
fetchThe fetch tool exposed by this server.
CustomizationThe Customization tool exposed by this server.
DebuggingEnable debug logging by modifying the logging level in main.py: python logging.basicConfig(level=logging.DEBUG)

How to install the MCP Fetch As Markdown MCP server

{
  "mcpServers": {
    "fetch-as-markdown": {
      "command": "uvx",
      "args": ["git+https://github.com/bhubbb/mcp-fetch-as-markdown"]
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Python 3.12 or higher - uv package manager

Example prompts to try

  • Use MCP Fetch As Markdown to Attribution.
  • Use MCP Fetch As Markdown to Prerequisites.
  • Use MCP Fetch As Markdown to fetch.

Frequently asked questions

It connects MCP Fetch As Markdown to MCP-compatible AI assistants such as Claude and Cursor, exposing 5 tools (Attribution, Prerequisites, fetch, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with MCP Fetch As Markdown directly.