🤖 AI Assistant with MCP + LangChain + Groq

This project demonstrates how to build a conversational AI assistant using MCP (Modular Chain Processor), LangChain, and Groq LLMs. It leverages memory-enabled agents and Groq-hosted LLMs to interactively respond to user queries in a smart and contextual way.

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📌 Features

• 🧠 Conversational memory (persistent session context)
• ⚙️ Integration with Groq's ultra-fast LLMs (Qwen, Mixtral, etc.)
• 🔄 Built using LangChain and MCP abstraction layers
• 💬 Interactive command-line chat interface
• ✅ Support for clearing history and exiting chat
• 🔒 Secure API Key loading from .env

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🛠️ Requirements

• Python 3.9 or later
• Groq API Key (sign up at Groq Cloud)
• MCP installed from source
• Optional: Create and activate a Python virtual environment

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📦 Installation

1. Clone this repo:

git clone https://github.com/your-username/ai-assistant-mcp-groq.git cd ai-assistant-mcp-groq

####2. Create a virtual environment and activate it: python -m venv env source env/bin/activate # On Linux/macOS env\Scripts\activate # On Windows

🔑 Environment Setup Create a .env file in the root directory and add your Groq API key:

GROQ_API_KEY=your_groq_api_key_here

🧠 Configuration Make sure you have a browser_mcp.json configuration file in your project directory. This file defines the behavior and tools of the MCP client.

{ "tools": ["search", "calendar", "weather"], "settings": { "max_retries": 3, "timeout_seconds": 20 } } Customize as needed for your use case.

▶️ Run the Assistant

python app.py

You will enter an interactive chat session:

You: Hello MCP: Hi there! How can I assist you today?

You: clear Conversation history cleared.

You: exit Exiting the chat.

📁 Project Structure pgsql Copy Edit . ├── app.py # Main application file ├── mcp_use.py # MCPAgent and MCPClient wrapper ├── browser_mcp.json # Tool configuration ├── .env # Your API key (not tracked by Git) ├── requirements.txt # Python dependencies └── README.md # This file

🚀 Example Use Cases

Ask about weather, calendar, and search information

Use AI for summarization, suggestions, and planning

Build a smart chat experience in any terminal app