🧠 CerebroMCP: Your AI Command Center

Intelligent AI Orchestration at Your Fingertips
A powerful system that combines the best of multiple AI technologies to deliver smart, context-aware responses.

✨ Why CerebroMCP?

Imagine having a team of AI experts at your disposal, each specialized in different tasks. CerebroMCP is exactly that - an intelligent system that:

• 🤖 Smartly Routes your queries to the most appropriate AI system
• 🧠 Learns & Remembers your conversation history
• 📚 Retrieves Information from your documents when needed
• 👥 Collaborates using multiple AI agents for complex tasks
• ⚡ Responds Instantly with the most relevant information

🚀 Quick Start

# Clone the repository
git clone https://github.com/yourusername/CerebroMCP.git
cd CerebroMCP

# Set up your environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

🏃‍♂️ Running the Application

Method 1: Using VS Code (Recommended)

1. Open the project in VS Code
2. Go to the Run and Debug view (Ctrl+Shift+D or Cmd+Shift+D)
3. Select "Run Full Application" from the dropdown
4. Click the play button or press F5

This will start both the persistent server and main application in debug mode.

Method 2: Manual Terminal

1. Start the persistent server in one terminal:

# Activate virtual environment if not already activated
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Start the persistent server
python app/servers/persistent_server.py

2. In another terminal, start the main application:

# Activate virtual environment if not already activated
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Start the main application
python app/main.py

Method 3: Using Scripts

You can also use the provided scripts to start the application:

# Start both server and main application
./scripts/start.sh  # On Windows: scripts\start.bat

🎯 How It Works

CerebroMCP uses intelligent routing to direct your queries to the most appropriate AI system:

📁 Project Structure

├── app/
│   ├── main.py              # 🎮 Main application
│   ├── clients/             # 🤝 AI client implementations
│   ├── servers/            # 🖥️  MCP server implementations
│   ├── host_managed/       # 🏠 Internal LLM implementations
│   └── memory/            # 💾 Conversation memory
├── .env                   # 🔑 Environment variables
├── requirements.txt       # 📦 Dependencies
└── memory.db             # 💿 SQLite database

🔧 Configuration

1. Create a .env file in the root directory
2. Add your API keys and configurations:

OPENAI_API_KEY=your_key_here
LLAMA_API_KEY=your_key_here
# Add other configurations as needed

🛠️ Dependencies

• mcp - Core MCP functionality
• openai - OpenAI API integration
• langgraph - Graph-based workflow management
• crewai - Multi-agent collaboration
• chromadb - Vector database for RAG
• And more... (see requirements.txt)

🤝 Contributing

We welcome contributions! Here's how you can help:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

📝 License

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

🌟 Star Us!

If you find CerebroMCP useful, please consider giving us a star on GitHub! It helps others discover the project.

Made with ❤️ by Prahlad