DuckDuckGo Search with MCP Agent

@alihassanml

代码仓库

基本信息

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许可证

MIT

传输方式

stdio

作者

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

DuckDuckGo Search with MCP Agent 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"
      ]
    }
  }
}

DuckDuckGo Search with MCP Agent 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

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

常见问题

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."

What transport protocol does the server use?

The server uses MCP (Micro Component Protocol) over stdio, launched via the `uvx` command.

Is there a license for this project?

Yes, this project is licensed under the MIT License.

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