GROQ

Overview

This project implements a suite of AI tools built on the Machine Communication Protocol (MCP) framework. Each tool leverages large language models through a client-server architecture to provide specialized functionality for search, mathematics, and news retrieval operations.

Features

• DuckDuckGo Search Engine: Web search with content extraction capabilities
• Mathematical Operations Engine: Basic arithmetic with natural language processing
• Tech News Aggregator: Real-time technology news from reputable sources

Requirements

• Python 3.8+
• UV package manager
• Groq API key

Installation

Setting up UV

If you don't have UV installed, install it first:

# Install UV using curl
curl -sSf https://install.ultraviolet.rs | sh

# Or with pip
pip install uv

Installing Project Dependencies

Clone the repository and install dependencies using the existing pyproject.toml:

# Clone the repository
git clone https://github.com/rahulsamant37/mcp-tools.git
cd mcp-tools

# Create and activate a virtual environment
uv venv
# On Windows:
.venv\Scripts\activate
# On macOS/Linux:
source .venv/bin/activate

# Install dependencies from pyproject.toml
uv pip sync

If you need to install dependencies without an existing pyproject.toml:

# Install directly (will update pyproject.toml and uv.lock)
uv pip install mcp langchain-mcp-adapters langchain-groq langgraph httpx beautifulsoup4 python-dotenv

Environment Configuration

Create a .env file in the project root:

GROQ_API_KEY=your_groq_api_key_here

Usage Guide

Each tool can be tested independently by running its client script, which automatically launches the corresponding server component.

DuckDuckGo Search Tool

python duckduckgo_client.py

This tool provides:

• Web search functionality via DuckDuckGo
• Content extraction from websites
• Rate-limited requests to prevent IP blocking
• Formatted search results optimized for LLM consumption

Math Calculation Tool

python math_client.py

This tool enables:

• Basic arithmetic operations (addition, multiplication)
• Natural language processing of mathematical expressions
• Integration with ReAct agents for complex problem solving

Tech News Retrieval Tool

python weather_client.py

This tool delivers:

• Latest articles from Ars Technica
• Content parsing and summarization
• Structured data output for LLM processing

Technical Architecture

The project implements a microservices architecture using MCP:

Server Layer

• Implements domain-specific functionality
• Exposes capabilities through standardized MCP interfaces
• Handles rate limiting and error management
• Processes raw data into LLM-friendly formats

Client Layer

• Establishes connections to server components
• Creates LangChain-compatible tool interfaces
• Integrates with ReAct agents for reasoning
• Manages conversation context and state

LLM Integration

• Leverages Groq's Qwen-2.5-32b model for reasoning
• Implements ReAct (Reasoning + Acting) methodology
• Supports asynchronous operations for improved performance

Troubleshooting

Issue	Solution
Connection errors	Check that no other processes are using required ports
Authentication failures	Verify Groq API key in .env file
Rate limiting	Implement exponential backoff between requests
Timeout errors	Increase timeout values in httpx client configurations
Dependency issues	Run uv pip list to verify installations
UV sync errors	Check if pyproject.toml exists and is valid

Contributing

To extend this project with new tools:

1. Create a server file implementing your tool's functionality
2. Expose methods using the @mcp.tool() decorator
3. Develop a client file that establishes connections and loads tools
4. Integrate with the ReAct agent framework

License

This project is licensed under the GNU License - see the LICENSE file for details.

Acknowledgments

• Machine Communication Protocol team
• langchain-mcp-adapters framework
• Groq for LLM API access