📌Overview

Purpose: The DuckDuckGo Search MCP server aims to provide efficient web search capabilities through DuckDuckGo along with enhanced content fetching and parsing features.

Overview: This Model Context Protocol (MCP) server enables users to perform web searches and retrieve content from DuckDuckGo, with built-in features that ensure compliance with rate limits and optimize results for large language models (LLMs).

Key Features:

• Web Search: Implements advanced rate limiting and formatting, allowing users to search DuckDuckGo effectively and receive organized results.

• Content Fetching: Facilitates the retrieval and parsing of webpage content with intelligent text extraction, making it easier to access relevant information.

• Rate Limiting: Provides built-in protection mechanisms against excessive requests for both search and content fetching to prevent service disruption.

• Error Handling: Features comprehensive mechanisms for error reporting and logging, ensuring reliability during operations.

• LLM-Friendly Output: Formats results specifically for seamless integration and consumption by large language models.

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DuckDuckGo Search MCP Server

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

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 search and content fetching.
• Error Handling: Comprehensive error handling and logging.
• LLM-Friendly Output: Results formatted specifically for large language model consumption.

Installation

Installing via Smithery

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

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

Installing via uv

Install directly 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:

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

3. Restart Claude Desktop.

Development

For local development, you can use the MCP CLI:

# Run with the MCP Inspector
mcp dev server.py

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

Available Tools

1. Search Tool

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

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

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.

Result Processing

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

Error Handling

• Comprehensive error catching and reporting.
• Detailed logging through MCP context.

Contributing

Issues and pull requests are welcome! Potential areas for improvement include:

• Additional search parameters (region, language, etc.).
• Enhanced content parsing options.
• Caching layer for frequently accessed content.

License

This project is licensed under the MIT License.