Install
$ agentstack add mcp-alihassanml-duckduckgo-with-mcp ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ● Environment & secrets Used
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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).
Features
- MCP Server Integration (DuckDuckGo search)
- Groq LLM (
deepseek-r1-distill-llama-70b) for reasoning - Async Python execution
- Simple and modular
Installation
- Clone the repository:
git clone https://github.com/alihassanml/Duckduckgo-with-MCP.git
cd Duckduckgo-with-MCP
- Install dependencies:
pip install -r requirements.txt
(Include libraries like langchain_groq, python-dotenv, etc. in your requirements.txt.)
- Set up your
.envfile:
GROQ_API_KEY=your_groq_api_key_here
- Install the MCP Server:
uvx -y duckduckgo-mcp-server
(Make sure uvx is installed. If not, install it.)
Usage
Run the main script:
python main.py
This will:
- Start the MCP client
- Connect to the
duckduckgo-mcp-server - Use the Groq LLM to perform a smart search
- Print the result
Example Code
import asyncio
import os
from dotenv import load_dotenv
from langchain_groq import ChatGroq
from mcp_use import MCPAgent, MCPClient
async def main():
load_dotenv()
config = {
"mcpServers": {
"ddg-search": {
"command": "uvx",
"args": ["-y", "duckduckgo-mcp-server"]
}
}
}
client = MCPClient.from_dict(config)
llm = ChatGroq(model="deepseek-r1-distill-llama-70b")
agent = MCPAgent(llm=llm, client=client, max_steps=30)
result = await agent.run("Find the best restaurant in San Francisco")
print(f"\nResult: {result}")
if __name__ == "__main__":
asyncio.run(main())
Resources
License
This project is licensed under the MIT License.
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: alihassanml
- Source: alihassanml/Duckduckgo-with-MCP
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.