duckduckgo-mcp 2.0.0

DuckDuckGo search and content retrieval tool for MCP (Model Context Protocol)

DuckDuckGo MCP Server

A Model Context Protocol (MCP) server that allows searching the web using DuckDuckGo. This package provides an easy way to integrate DuckDuckGo search functionality into your Python applications and LLM workflows.

Features

• Search the web using DuckDuckGo
• Return structured results with titles, URLs, and snippets
• Configurable number of results
• Implemented using FastMCP library with STDIO transport

Installation

Prerequisites

• Python 3.10 or higher
• uv (recommended) or pip

Install from PyPI (recommended)

# Using uv (recommended)
uv pip install duckduckgo-mcp

# Or using pip
pip install duckduckgo-mcp

Install with UVX (for Claude Desktop)

# Install UVX if you haven't already
pip install uvx

# Install the DuckDuckGo MCP package
uvx install duckduckgo-mcp

Install from source

For development or to get the latest changes:

# Clone the repository
git clone https://github.com/CyranoB/duckduckgo-mcp.git
cd duckduckgo-mcp

# Install with uv (recommended)
uv pip install -e .

# Or with pip
pip install -e .

Usage

Starting the Server (STDIO Mode)

# Start the server in STDIO mode (for use with MCP clients like Claude)
duckduckgo-mcp serve

# Enable debug logging
duckduckgo-mcp serve --debug

Testing the Search Tool

You can test the search functionality directly from the command line:

# Search DuckDuckGo
duckduckgo-mcp search "your search query" --max-results 5

Integration with LLM Tools

This MCP server is designed to work with any LLM tool that supports the Model Context Protocol (MCP).

Using with Claude CLI

1. Install the package using one of the methods above

2. Use it with Claude CLI:

   claude code --mcp duckduckgo-mcp
   

   Or with the full path:

   claude code --mcp $(which duckduckgo-mcp)
   

Using with Claude Desktop

1. Install the package with UVX as described above

2. Add it to Claude Desktop (recommended method):

   claude mcp add duckduckgo -- uvx --python=3.10 duckduckgo-mcp serve
   

3. Alternatively, manually edit the Claude Desktop configuration file:

   The configuration file is located at:

   • macOS: ~/.claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json
   • Linux: ~/.config/Claude/claude_desktop_config.json

   Add the following to your configuration file:

   {
     "mcpServers": {
       "duckduckgo": {
         "command": "uvx",
         "args": ["--python=3.10", "duckduckgo-mcp", "serve"]
       }
     }
   }
   

4. Start a new session in Claude Desktop and select the DuckDuckGo tool from available MCPs

MCP Integration

When using with an MCP client (like Claude), the server exposes a single tool:

@mcp.tool()
def search(query: str, max_results: int = 5) -> list:
    """Search DuckDuckGo for the given query.
    
    Args:
        query: The search query string
        max_results: Maximum number of results to return (default: 5)
        
    Returns:
        List of search results with title, url, and snippet for each result
    """

Example usage in an MCP client:

# This is handled automatically by the MCP client
results = search("Python programming", max_results=3)

Contributing

Contributions are welcome! Here's how you can contribute:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

API

The MCP server exposes a single tool:

• Tool Name: duckduckgo_search
• Description: Search the web using DuckDuckGo

Parameters

• query (string, required): The search query
• max_results (integer, optional, default: 5): Maximum number of search results to return

Response

{
  "results": [
    {
      "title": "Result title",
      "url": "https://example.com",
      "snippet": "Text snippet from the search result"
    },
    ...
  ]
}

Contributing

Contributions are welcome! Here's how you can contribute:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Support

If you encounter any issues or have questions, please open an issue.

License

This project is licensed under the MIT License - see the LICENSE file for details.