ddg-mcp MCP server

DuckDuckGo search API MCP - A server that provides DuckDuckGo search capabilities through the Model Context Protocol.

Components

Prompts

The server provides the following prompts:

• search-results-summary: Creates a summary of DuckDuckGo search results

  • Required "query" argument for the search term

  • Optional "style" argument to control detail level (brief/detailed)

Tools

The server implements the following DuckDuckGo search tools:

• ddg-text-search: Search the web for text results using DuckDuckGo

  • Required: "keywords" - Search query keywords

  • Optional: "region", "safesearch", "timelimit", "max_results"

• ddg-image-search: Search the web for images using DuckDuckGo

  • Required: "keywords" - Search query keywords

  • Optional: "region", "safesearch", "timelimit", "size", "color", "type_image", "layout", "license_image", "max_results"

• ddg-news-search: Search for news articles using DuckDuckGo

  • Required: "keywords" - Search query keywords

  • Optional: "region", "safesearch", "timelimit", "max_results"

• ddg-video-search: Search for videos using DuckDuckGo

  • Required: "keywords" - Search query keywords

  • Optional: "region", "safesearch", "timelimit", "resolution", "duration", "license_videos", "max_results"

• ddg-ai-chat: Chat with DuckDuckGo AI

  • Required: "keywords" - Message or question to send to the AI

  • Optional: "model" - AI model to use (options: "gpt-4o-mini", "llama-3.3-70b", "claude-3-haiku", "o3-mini", "mistral-small-3")

Installation

Prerequisites

• Python 3.9 or higher

• uv (recommended) or pip

Install from PyPI

Install from Source

1. Clone the repository:

2. Install the package:

Configuration

Required Dependencies

The server requires the duckduckgo-search package, which will be installed automatically when you install ddg-mcp.

If you need to install it manually:

DuckDuckGo Search Parameters

Common Parameters

These parameters are available for most search types:

• region: Region code for localized results (default: "wt-wt")

  • Examples: "us-en" (US English), "uk-en" (UK English), "ru-ru" (Russian)

  • See DuckDuckGo regions for more options

• safesearch: Content filtering level (default: "moderate")

  • "on": Strict filtering

  • "moderate": Moderate filtering

  • "off": No filtering

• timelimit: Time range for results

  • "d": Last day

  • "w": Last week

  • "m": Last month

  • "y": Last year (not available for news/videos)

• max_results: Maximum number of results to return (default: 10)

Search Operators

You can use these operators in your search keywords:

• cats dogs: Results about cats or dogs

• "cats and dogs": Results for exact term "cats and dogs"

• cats -dogs: Fewer dogs in results

• cats +dogs: More dogs in results

• cats filetype:pdf: PDFs about cats (supported: pdf, doc(x), xls(x), ppt(x), html)

• dogs site:example.com: Pages about dogs from example.com

• cats -site:example.com: Pages about cats, excluding example.com

• intitle:dogs: Page title includes the word "dogs"

• inurl:cats: Page URL includes the word "cats"

Image Search Specific Parameters

• size: "Small", "Medium", "Large", "Wallpaper"

• color: "color", "Monochrome", "Red", "Orange", "Yellow", "Green", "Blue", "Purple", "Pink", "Brown", "Black", "Gray", "Teal", "White"

• type_image: "photo", "clipart", "gif", "transparent", "line"

• layout: "Square", "Tall", "Wide"

• license_image: "any", "Public", "Share", "ShareCommercially", "Modify", "ModifyCommercially"

Video Search Specific Parameters

• resolution: "high", "standard"

• duration: "short", "medium", "long"

• license_videos: "creativeCommon", "youtube"

AI Chat Models

• gpt-4o-mini: OpenAI's GPT-4o mini model

• llama-3.3-70b: Meta's Llama 3.3 70B model

• claude-3-haiku: Anthropic's Claude 3 Haiku model

• o3-mini: OpenAI's O3 mini model

• mistral-small-3: Mistral AI's small model

Quickstart

Install

Claude Desktop

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

Usage Examples

Text Search

Advanced example:

Image Search

Advanced example:

News Search

Advanced example:

Video Search

Advanced example:

AI Chat

Search Results Summary

Claude config

"ddg-mcp": { "command": "uv", "args": [ "--directory", "/PATH/TO/YOUR/INSTALLATION/ddg-mcp", "run", "ddg-mcp" ] },

Development

Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:

2. Build package distributions:

This will create source and wheel distributions in the dist/ directory.

3. Publish to PyPI:

Note: You'll need to set PyPI credentials via environment variables or command flags:

• Token: --token or UV_PUBLISH_TOKEN

• Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Automated Publishing with GitHub Actions

This repository includes a GitHub Actions workflow for automated publishing to PyPI. The workflow is triggered when:

1. A new GitHub Release is created

2. The workflow is manually triggered via the GitHub Actions interface

To set up automated publishing:

1. Generate a PyPI API token:

   • Go to https://pypi.org/manage/account/token/

   • Create a new token with scope limited to the ddg-mcp project

   • Copy the token value (you'll only see it once)

2. Add the token to your GitHub repository secrets:

   • Go to your repository on GitHub

   • Navigate to Settings > Secrets and variables > Actions

   • Click "New repository secret"

   • Name: PYPI_API_TOKEN

   • Value: Paste your PyPI token

   • Click "Add secret"

3. To publish a new version:

   • Update the version number in pyproject.toml

   • Create a new release on GitHub or manually trigger the workflow

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.