search-web

DuckDuckGo Search

by nickclyde

DuckDuckGo Search integrates web search and content parsing, ensuring privacy-focused results for large language model u

Integrates with DuckDuckGo to provide web search capabilities, content fetching, and parsing, with results formatted for large language model consumption.

github stars

863

Repository deprecated - use mcp-omnisearch insteadMultiple result types supported

best for

  • / LLM applications needing web search
  • / Research and information gathering
  • / Content discovery workflows

capabilities

  • / Search web content using DuckDuckGo
  • / Filter results by date and region
  • / Retrieve news articles and video content
  • / Configure safe search levels
  • / Paginate through search results
  • / Cache search results

what it does

Provides web search functionality through DuckDuckGo with support for different result types, filtering, and pagination. Note: This repository is deprecated in favor of mcp-omnisearch.

about

DuckDuckGo Search is a community-built MCP server published by nickclyde that provides AI assistants with tools and capabilities via the Model Context Protocol. DuckDuckGo Search integrates web search and content parsing, ensuring privacy-focused results for large language model u It is categorized under search web. This server exposes 2 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install DuckDuckGo Search in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport. This server supports remote connections over HTTP, so no local installation is required.

license

MIT

DuckDuckGo Search is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

DuckDuckGo Search MCP Server

PyPI version PyPI downloads Python versions

A Model Context Protocol (MCP) server that provides web search capabilities through DuckDuckGo, with additional features for content fetching and parsing.

Quick Start

uvx duckduckgo-mcp-server

Features

  • Web Search: Search DuckDuckGo with advanced rate limiting and result formatting
  • Content Fetching: Retrieve and parse webpage content with intelligent text extraction
  • Rate Limiting: Built-in protection against rate limits for both search and content fetching
  • Error Handling: Comprehensive error handling and logging
  • LLM-Friendly Output: Results formatted specifically for large language model consumption

Installation

Install from PyPI using uv:

uv pip install duckduckgo-mcp-server

Usage

Running with Claude Desktop

  1. Download Claude Desktop
  2. Create or edit your Claude Desktop configuration:
    • On macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • On Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the following configuration:

Basic Configuration (No SafeSearch, No Default Region):

{
    "mcpServers": {
        "ddg-search": {
            "command": "uvx",
            "args": ["duckduckgo-mcp-server"]
        }
    }
}

With SafeSearch and Region Configuration:

{
    "mcpServers": {
        "ddg-search": {
            "command": "uvx",
            "args": ["duckduckgo-mcp-server"],
            "env": {
                "DDG_SAFE_SEARCH": "STRICT",
                "DDG_REGION": "cn-zh"
            }
        }
    }
}

Configuration Options:

  • DDG_SAFE_SEARCH: SafeSearch filtering level (optional)
    • STRICT: Maximum content filtering (kp=1)
    • MODERATE: Balanced filtering (kp=-1, default if not specified)
    • OFF: No content filtering (kp=-2)
  • DDG_REGION: Default region/language code (optional, examples below)
    • us-en: United States (English)
    • cn-zh: China (Chinese)
    • jp-ja: Japan (Japanese)
    • wt-wt: No specific region
    • Leave empty for DuckDuckGo's default behavior
  1. Restart Claude Desktop

Running with Claude Code

  1. Download Claude Code
  2. Ensure uvenv is installed and the uvx command is available
  3. Add the MCP server: claude mcp add ddg-search uvx duckduckgo-mcp-server

Running with SSE or Streamable HTTP

The server supports alternative transports for use with other MCP clients:

# SSE transport
uvx duckduckgo-mcp-server --transport sse

# Streamable HTTP transport
uvx duckduckgo-mcp-server --transport streamable-http

The default transport is stdio, which is used by Claude Desktop and Claude Code.

Development

For local development:

# Install dependencies
uv sync

# Run with the MCP Inspector
mcp dev src/duckduckgo_mcp_server/server.py

# Install locally for testing with Claude Desktop
mcp install src/duckduckgo_mcp_server/server.py

# Run all tests
uv run python -m pytest src/duckduckgo_mcp_server/ -v

# Run only unit tests
uv run python -m pytest src/duckduckgo_mcp_server/test_server.py -v

# Run only e2e tests
uv run python -m pytest src/duckduckgo_mcp_server/test_e2e.py -v

Available Tools

1. Search Tool

async def search(query: str, max_results: int = 10, region: str = "") -> str

Performs a web search on DuckDuckGo and returns formatted results.

Parameters:

  • query: Search query string
  • max_results: Maximum number of results to return (default: 10)
  • region: (Optional) Region/language code to override the default. Leave empty to use the configured default region.

Region Code Examples:

  • us-en: United States (English)
  • cn-zh: China (Chinese)
  • jp-ja: Japan (Japanese)
  • de-de: Germany (German)
  • fr-fr: France (French)
  • wt-wt: No specific region

Returns: Formatted string containing search results with titles, URLs, and snippets.

Example Usage:

  • Search with default settings: search("python tutorial")
  • Search with specific region: search("latest news", region="jp-ja") for Japanese news

2. Content Fetching Tool

async def fetch_content(url: str) -> str

Fetches and parses content from a webpage.

Parameters:

  • url: The webpage URL to fetch content from

Returns: Cleaned and formatted text content from the webpage.

Features in Detail

Rate Limiting

  • Search: Limited to 30 requests per minute
  • Content Fetching: Limited to 20 requests per minute
  • Automatic queue management and wait times

Result Processing

  • Removes ads and irrelevant content
  • Cleans up DuckDuckGo redirect URLs
  • Formats results for optimal LLM consumption
  • Truncates long content appropriately

Content Safety

  • SafeSearch Filtering: Configured at server startup via DDG_SAFE_SEARCH environment variable

    • Controlled by administrators, not modifiable by AI assistants
    • Filters inappropriate content based on the selected level
    • Uses DuckDuckGo's official kp parameter
  • Region Localization:

    • Default region set via DDG_REGION environment variable
    • Can be overridden per search request by AI assistants
    • Improves result relevance for specific geographic regions

Error Handling

  • Comprehensive error catching and reporting
  • Detailed logging through MCP context
  • Graceful degradation on rate limits or timeouts

Contributing

Issues and pull requests are welcome! Some areas for potential improvement:

  • Enhanced content parsing options
  • Caching layer for frequently accessed content
  • Additional rate limiting strategies

License

This project is licensed under the MIT License.