MCP Tools Project

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

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