duckduckgo-mcp

duckduckgo-mcp

Search the web using DuckDuckGo and fetch/convert web content using Jina Reader. Privacy-focused search with no API key required.

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README

DuckDuckGo MCP Server

PyPI Python Version License: MIT Downloads Smithery

A Model Context Protocol (MCP) server that provides two capabilities:

  1. Search the web using DuckDuckGo
  2. Fetch and convert web content using Jina Reader

Features

  • DuckDuckGo web search with safe search controls
  • Fetch and convert URLs to markdown or JSON using Jina Reader
  • LLM-friendly output format option for search results
  • CLI for search, fetch, serve, and version commands
  • MCP tools for LLM integration
  • Docker support for containerized deployment

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 via Smithery

To install DuckDuckGo MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @cyranob/duckduckgo-mcp --client claude

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 .

Docker

Build and run with Docker:

# Build the image (uses version from latest git tag)
docker build --build-arg VERSION=$(git describe --tags --abbrev=0 | sed 's/^v//') -t duckduckgo-mcp .

# Or specify a version manually
docker build --build-arg VERSION=2.0.2 -t duckduckgo-mcp .

# Run the server (MCP servers use STDIO, so typically run within an MCP client)
docker run -i duckduckgo-mcp

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

# Search DuckDuckGo (JSON output, default)
duckduckgo-mcp search "your search query" --max-results 5 --safesearch moderate

# Search with LLM-friendly text output
duckduckgo-mcp search "your search query" --output-format text

Testing the Fetch Tool

# Fetch a URL and return markdown
duckduckgo-mcp fetch "https://example.com" --format markdown

# Fetch a URL and return JSON
duckduckgo-mcp fetch "https://example.com" --format json

# Limit output length

duckduckgo-mcp fetch "https://example.com" --max-length 2000

# Include generated image alt text
duckduckgo-mcp fetch "https://example.com" --with-images

Version Information

# Show version
duckduckgo-mcp version

# Show detailed version info
duckduckgo-mcp version --debug

MCP Client Setup

This MCP server works with any MCP-compatible client. Use one of the setups below.

Python 3.10-3.13 is supported (3.14 not yet). Use --python ">=3.10,<3.14" with uvx to enforce. Verified with Python 3.12 and 3.13.

Claude Desktop

  1. Open Claude Desktop > Settings > Developer > Edit Config.
  2. Edit the config file:
    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  3. Add the server config under mcpServers:
     {
       "mcpServers": {
         "duckduckgo": {
           "command": "uvx",
           "args": ["--python", ">=3.10,<3.14", "duckduckgo-mcp", "serve"]
         }
       }
     }
    
    
  4. Restart Claude Desktop.

Claude Code

Add a local stdio server:

claude mcp add --transport stdio duckduckgo -- uvx --python ">=3.10,<3.14" duckduckgo-mcp serve

Optional: claude mcp list to verify, or claude mcp add-from-claude-desktop to import.

Codex (CLI + IDE)

Add via CLI:

codex mcp add duckduckgo -- uvx --python ">=3.10,<3.14" duckduckgo-mcp serve

Or configure ~/.codex/config.toml:

[mcp_servers.duckduckgo]
command = "uvx"
args = ["--python", ">=3.10,<3.14", "duckduckgo-mcp", "serve"]

OpenCode

Add to your OpenCode config (~/.config/opencode/opencode.json or project opencode.json):

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "duckduckgo": {
      "type": "local",
      "command": ["uvx", "--python", ">=3.10,<3.14", "duckduckgo-mcp", "serve"],
      "enabled": true
    }
  }
}

Or run opencode mcp add and follow the prompts.

Cursor

Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project):

{
  "mcpServers": {
    "duckduckgo": {
      "command": "uvx",
      "args": ["--python", ">=3.10,<3.14", "duckduckgo-mcp", "serve"]
    }
  }
}

Verify with:

cursor-agent mcp list

MCP Tools

The server exposes these tools to MCP clients:

@mcp.tool()
def duckduckgo_search(
    query: str,
    max_results: int = 5,
    safesearch: str = "moderate",
    output_format: str = "json"
) -> list | str:
    """Search DuckDuckGo for the given query."""
@mcp.tool()
def jina_fetch(url: str, format: str = "markdown", max_length: int | None = None, with_images: bool = False) -> str | dict:
    """Fetch a URL and convert it using Jina Reader."""

Example usage in an MCP client:

# This is handled automatically by the MCP client
results = duckduckgo_search("Python programming", max_results=3)
content = jina_fetch("https://example.com", format="markdown")

# Get LLM-friendly text output
text_results = duckduckgo_search("Python programming", output_format="text")

API

Tool 1: Search

  • Tool Name: duckduckgo_search
  • Description: Search the web using DuckDuckGo (powered by the ddgs library)

Parameters

  • query (string, required): The search query
  • max_results (integer, optional, default: 5): Maximum number of search results to return
  • safesearch (string, optional, default: "moderate"): Safe search setting ("on", "moderate", or "off")
  • output_format (string, optional, default: "json"): Output format - "json" for structured data, "text" for LLM-friendly formatted string

Response

JSON format (default): A list of dictionaries:

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

Text format: An LLM-friendly formatted string:

Found 3 search results:

1. Result title
   URL: https://example.com
   Summary: Text snippet from the search result

2. Another result
   URL: https://example2.com
   Summary: Another snippet

Tool 2: Fetch

  • Tool Name: jina_fetch
  • Description: Fetch a URL and convert it to markdown or JSON using Jina Reader

Parameters

  • url (string, required): The URL to fetch and convert
  • format (string, optional, default: "markdown"): Output format ("markdown" or "json")
  • max_length (integer, optional): Maximum content length to return (None for no limit)
  • with_images (boolean, optional, default: false): Whether to include image alt text generation

Response

For markdown format: a string containing markdown content

For JSON format: a dictionary with the structure:

{
  "url": "https://example.com",
  "title": "Page title",
  "content": "Markdown content"
}

Notes

  • Search uses the ddgs package (renamed from duckduckgo-search).
  • Fetch uses the Jina Reader API at https://r.jina.ai/.

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.

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