DuckDuckGo Search MCP Server

DuckDuckGo Search MCP Server

By nickclyde GitHub

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

Overview

what is DuckDuckGo Search MCP Server?

DuckDuckGo Search MCP Server is a Model Context Protocol (MCP) server that provides web search capabilities through DuckDuckGo, along with features for content fetching and parsing.

how to use DuckDuckGo Search MCP Server?

To use the server, install it via PyPI using the command uv pip install duckduckgo-mcp-server, and configure it with Claude Desktop by editing the configuration file to include the MCP server settings.

key features of DuckDuckGo Search MCP Server?

  • Web search with advanced rate limiting and result formatting
  • Content fetching with intelligent text extraction
  • Built-in rate limiting protection
  • Comprehensive error handling and logging
  • LLM-friendly output formatting

use cases of DuckDuckGo Search MCP Server?

  1. Performing web searches with formatted results for applications.
  2. Fetching and parsing content from webpages for data analysis.
  3. Integrating search capabilities into other applications using the MCP protocol.

FAQ from DuckDuckGo Search MCP Server?

  • Can I use this server for any web search?

Yes! It is designed to perform searches specifically through DuckDuckGo.

  • Is there a limit on the number of requests?

Yes, the server has rate limits: 30 requests per minute for search and 20 for content fetching.

  • How do I handle errors?

The server includes comprehensive error handling and logging to help diagnose issues.

Content

DuckDuckGo Search MCP Server

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

DuckDuckGo Server 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

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"]
        }
    }
}
  1. 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
  • 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

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:

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

License

This project is licensed under the MIT License.

No tools information available.
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