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Fetch Python

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Fetch Python — Model Context Protocol server

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About

Fetch Python — Model Context Protocol server

README

An MCP server for fetching and transforming web content into various formats. This server provides comprehensive tools for extracting content from web pages, including support for JavaScript-rendered content and media files.

Server Fetch Python MCP server

Features

Tools

The server provides four specialized tools:

  • get-raw-text: Extracts raw text content directly from URLs without browser rendering

    • Arguments:
      • url: URL of the target web page (text, JSON, XML, csv, tsv, etc.) (required)
    • Best used for structured data formats or when fast, direct access is needed
  • get-rendered-html: Fetches fully rendered HTML content using a headless browser

    • Arguments:
      • url: URL of the target web page (required)
    • Essential for modern web applications and SPAs that require JavaScript rendering
  • get-markdown: Converts web page content to well-formatted Markdown

    • Arguments:
      • url: URL of the target web page (required)
    • Preserves structural elements while providing clean, readable text output
  • get-markdown-from-media: Performs AI-powered content extraction from media files

    • Arguments:
      • url: URL of the target media file (images, videos) (required)
    • Utilizes computer vision and OCR for visual content analysis
    • Requires a valid OPENAI_API_KEY to be set in environment variables
    • Will return an error message if the API key is not set or if there are issues processing the media file

Usage

Claude Desktop

To use with Claude Desktop, add the server configuration:

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

"mcpServers": {
  "mcp-server-fetch-python": {
    "command": "uvx",
    "args": [
      "mcp-server-fetch-python"
    ]
  }
}

Environment Variables

The following environment variables can be configured:

  • OPENAI_API_KEY: Required for using the get-markdown-from-media tool. This key is needed for AI-powered image analysis and content extraction.
  • PYTHONIOENCODING: Set to "utf-8" if you encounter character encoding issues in the output.
  • MODEL_NAME: Specifies the model name to use. Defaults to "gpt-4o".
"mcpServers": {
  "mcp-server-fetch-python": {
    "command": "uvx",
    "args": [
      "mcp-server-fetch-python"
    ],
    "env": {
        "OPENAI_API_KEY": "sk-****",
        "PYTHONIOENCODING": "utf-8",
        "MODEL_NAME": "gpt-4o",        
    }
  }
}

Local Installation

Alternatively, you can install and run the server locally:

git clone https://github.com/tatn/mcp-server-fetch-python.git
cd mcp-server-fetch-python
uv sync
uv build

Then add the following configuration to Claude Desktop config file:

"mcpServers": {
  "mcp-server-fetch-python": {
    "command": "uv",
    "args": [
      "--directory",
      "path\\to\\mcp-server-fetch-python",  # Replace with actual path to the cloned repository
      "run",
      "mcp-server-fetch-python"
    ]
  }
}

Development

Debugging

You can start the MCP Inspector using npxwith the following commands:

npx @modelcontextprotocol/inspector uvx mcp-server-fetch-python
npx @modelcontextprotocol/inspector uv --directory path\\to\\mcp-server-fetch-python run mcp-server-fetch-python

from github.com/tatn/mcp-server-fetch-python

Installing Fetch Python

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/tatn/mcp-server-fetch-python

FAQ

Is Fetch Python MCP free?

Yes, Fetch Python MCP is free — one-click install via Unyly at no cost.

Does Fetch Python need an API key?

No, Fetch Python runs without API keys or environment variables.

Is Fetch Python hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Fetch Python in Claude Desktop, Claude Code or Cursor?

Open Fetch Python on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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