DuckDuckGo Search with MCP Agent

Name: DuckDuckGo Search with MCP Agent
Author: alihassanml

@alihassanml

关于 DuckDuckGo Search with MCP Agent

This project demonstrates how to use DuckDuckGo MCP Server with a LangChain Groq LLM agent to perform intelligent search tasks via MCP (Micro Component Protocol).

#duckduckgo #mcp-server

基本信息

分类

搜索

许可证

MIT

运行时

python

传输方式

stdio

发布者

alihassanml

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "Duckduckgo-with-MCP": {
      "command": "uvx",
      "args": [
        "-y",
        "duckduckgo-mcp-server"
      ]
    }
  }
}

工具

未检测到工具

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概览

What is DuckDuckGo Search with MCP Agent?

DuckDuckGo Search with MCP Agent is a project that demonstrates how to use the DuckDuckGo MCP Server with a LangChain Groq LLM agent to perform intelligent search tasks via MCP (Micro Component Protocol). It is intended for developers building search-driven applications with agentic reasoning.

How to use DuckDuckGo Search with MCP Agent?

Clone the repository, install dependencies with pip install -r requirements.txt, set your GROQ_API_KEY in a .env file, install the MCP server via uvx -y duckduckgo-mcp-server, and run python main.py. The script starts an MCP client, connects to the DuckDuckGo MCP server, and uses the Groq LLM to perform a smart search.

Key features of DuckDuckGo Search with MCP Agent

DuckDuckGo MCP Server integration
Groq LLM (deepseek-r1-distill-llama-70b) for reasoning
Async Python execution
Simple and modular code structure

Use cases of DuckDuckGo Search with MCP Agent

Performing intelligent web searches with an LLM agent
Demonstrating MCP client-server integration with LangChain
Building modular search pipelines that reason over results

FAQ from DuckDuckGo Search with MCP Agent

What dependencies are required?

The project requires libraries such as langchain_groq and python-dotenv, listed in requirements.txt. You also need uvx installed to run the DuckDuckGo MCP server.

What LLM model does the agent use?

The agent uses Groq's deepseek-r1-distill-llama-70b model for reasoning.

How do I get started quickly?

Set up your .env file with a valid GROQ_API_KEY, install all Python dependencies, and run python main.py. The script includes an example that searches for "the best restaurant in San Francisco."