Enables large language models to fetch and retrieve content from URLs with support for multiple content types, customizable request parameters, and seamless integration with Claude Code and Claude Desktop using the Model Context Protocol.
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A clean Model Context Protocol (MCP) implementation that enables Claude or any LLM to fetch content from URLs.
url-fetch-mcp/
├── examples/ # Example scripts and usage demos
├── scripts/ # Helper scripts (installation, etc.)
├── src/
│ └── url_fetch_mcp/ # Main package code
│ ├── __init__.py
│ ├── __main__.py
│ ├── cli.py # Command-line interface
│ ├── fetch.py # URL fetching utilities
│ ├── main.py # Core MCP server implementation
│ └── utils.py # Helper utilities
├── LICENSE
├── pyproject.toml # Project configuration
├── README.md
└── url_fetcher.py # Standalone launcher for Claude Desktop
# Install from source pip install -e . # Install with development dependencies pip install -e ".[dev]"
# Run with stdio transport (for Claude Code) python -m url_fetch_mcp run # Run with HTTP+SSE transport (for remote connections) python -m url_fetch_mcp run --transport sse --port 8000
There are three ways to install in Claude Desktop:
# Install the package pip install -e . # Install in Claude Desktop using the included script mcp install url_fetcher.py -n "URL Fetcher"
The url_fetcher.py
file contains:
#!/usr/bin/env python """ URL Fetcher MCP Server This is a standalone script for launching the URL Fetch MCP server. It's used for installing in Claude Desktop with the command: mcp install url_fetcher.py -n "URL Fetcher" """ from url_fetch_mcp.main import app if __name__ == "__main__": app.run()
# Install the package pip install -e . # Run the installer script python scripts/install_desktop.py
The scripts/install_desktop.py
script:
#!/usr/bin/env python import os import sys import tempfile import subprocess def install_desktop(): """Install URL Fetch MCP in Claude Desktop.""" print("Installing URL Fetch MCP in Claude Desktop...") # Create a temporary Python file that imports our module temp_dir = tempfile.mkdtemp() temp_file = os.path.join(temp_dir, "url_fetcher.py") with open(temp_file, "w") as f: f.write("""#!/usr/bin/env python # URL Fetcher MCP Server from url_fetch_mcp.main import app if __name__ == "__main__": app.run() """) # Make the file executable os.chmod(temp_file, 0o755) # Run the mcp install command with the file path try: cmd = ["mcp", "install", temp_file, "-n", "URL Fetcher"] print(f"Running: {' '.join(cmd)}") result = subprocess.run(cmd, check=True, text=True) print("Installation successful!") print("You can now use the URL Fetcher tool in Claude Desktop.") return 0 except subprocess.CalledProcessError as e: print(f"Error during installation: {str(e)}") return 1 finally: # Clean up temporary file try: os.unlink(temp_file) os.rmdir(temp_dir) except: pass if __name__ == "__main__": sys.exit(install_desktop())
# Install the package pip install -e . # Install using the built-in CLI command python -m url_fetch_mcp install-desktop
The main MCP implementation is in src/url_fetch_mcp/main.py
:
from typing import Annotated, Dict, Optional import base64 import json import httpx from pydantic import AnyUrl, Field from mcp.server.fastmcp import FastMCP, Context # Create the MCP server app = FastMCP( name="URL Fetcher", version="0.1.0", description="A clean MCP implementation for fetching content from URLs", ) @app.tool() async def fetch_url( url: Annotated[AnyUrl, Field(description="The URL to fetch")], headers: Annotated[ Optional[Dict[str, str]], Field(description="Additional headers to send with the request") ] = None, timeout: Annotated[int, Field(description="Request timeout in seconds")] = 10, ctx: Context = None, ) -> str: """Fetch content from a URL and return it as text.""" # Implementation details... @app.tool() async def fetch_image( url: Annotated[AnyUrl, Field(description="The URL to fetch the image from")], timeout: Annotated[int, Field(description="Request timeout in seconds")] = 10, ctx: Context = None, ) -> Dict: """Fetch an image from a URL and return it as an image.""" # Implementation details... @app.tool() async def fetch_json( url: Annotated[AnyUrl, Field(description="The URL to fetch JSON from")], headers: Annotated[ Optional[Dict[str, str]], Field(description="Additional headers to send with the request") ] = None, timeout: Annotated[int, Field(description="Request timeout in seconds")] = 10, ctx: Context = None, ) -> str: """Fetch JSON from a URL, parse it, and return it formatted.""" # Implementation details...
Fetches content from a URL and returns it as text.
Parameters:
url
(required): The URL to fetchheaders
(optional): Additional headers to send with the requesttimeout
(optional): Request timeout in seconds (default: 10)Fetches an image from a URL and returns it as an image.
Parameters:
url
(required): The URL to fetch the image fromtimeout
(optional): Request timeout in seconds (default: 10)Fetches JSON from a URL, parses it, and returns it formatted.
Parameters:
url
(required): The URL to fetch JSON fromheaders
(optional): Additional headers to send with the requesttimeout
(optional): Request timeout in seconds (default: 10)The examples
directory contains example scripts:
quick_test.py
: Quick test of the MCP serversimple_usage.py
: Example of using the client APIinteractive_client.py
: Interactive CLI for testing# Example of fetching a URL result = await session.call_tool("fetch_url", { "url": "https://example.com" }) # Example of fetching JSON data result = await session.call_tool("fetch_json", { "url": "https://api.example.com/data", "headers": {"Authorization": "Bearer token"} }) # Example of fetching an image result = await session.call_tool("fetch_image", { "url": "https://example.com/image.jpg" })
To test basic functionality:
# Run a direct test of URL fetching python direct_test.py # Run a simplified test with the MCP server python examples/quick_test.py
MIT
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