AI Assistant (ai-assistant-mcp)

AI Assistant with LangChain, Groq & MCP

This project is an AI Assistant built using LangChain, LangChain-Groq, and FastAPI, enhanced with MCP servers for additional functionality such as web automation, weather data, and academic paper search.

Features

• Conversational AI using Groq Chat model
• Exposed API endpoints via FastAPI
• Asynchronous communication using aiohttp and WebSockets
• Environment-based configuration via python-dotenv
• Integration with MCP servers: browser automation, weather API, and Semantic Scholar API

Tools & Technologies

AI & LLM Frameworks

• LangChain → Orchestrates language models, chains, and memory
• LangChain-Groq → Provides Groq Chat model integration

Web & API Frameworks

• FastAPI → Serves the AI Assistant as HTTP endpoints
• Uvicorn → ASGI server to run FastAPI apps
• aiohttp & websockets → For asynchronous HTTP requests and real-time communication

Environment & Dependency Management

• python-dotenv → Loads API keys and environment variables from .env
• venv → Isolated Python virtual environment for dependencies

MCP (Modular Chat Platform) Tools

• mcp-use → Manages and runs multiple MCP agents locally or remotely
• MCP Servers in this project:

- Playwright MCP Server → Browser automation and web scraping - MCP Weather Server → Fetches weather information dynamically - MCP Semantic Scholar Server → Academic paper metadata and search

Note: API keys are stored in .env and should never be pushed to GitHub. Use .env.example with placeholders for sharing.

Project Structure

AIAssistantWithMCP/
│ app.py # FastAPI entrypoint
│ requirements.txt # Python dependencies
│ .env # Environment variables (API keys)
│ venv/ # Virtual environment
│ README.md
│
├── mcp_servers/ # MCP server configurations
└── modules/ # Custom Python modules (if any)

Installation

# 1. Clone the repo
git clone https://github.com/maryemchk/ai-assistant-mcp.git
cd ai-assistant-mcp

# 2. Create a virtual environment
python -m venv venv
.\venv\Scripts\Activate.ps1  # Windows PowerShell
# OR
source venv/bin/activate      # Mac/Linux

# 3. Install dependencies
pip install -r requirements.txt

# 4. Create .env file from template
copy .env.example .env
# Fill in your API keys

License

MIT License

Acknowledgements

• LangChain
• Groq
• FastAPI
• MCP