A Model Context Protocol (MCP) server that enables Claude or other LLMs to fetch content from URLs, supporting HTML, JSON, text, and images with configurable request parameters.
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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