🦉 OWL x WhatsApp MCP Server Integration

🦉 OWL x WhatsApp MCP Server Integration

Welcome to the OWL x WhatsApp MCP Server project! This application seamlessly integrates the WhatsApp MCP server with the OWL multi-agent framework, enabling AI agents to interact with your WhatsApp data through a user-friendly Streamlit interface.

✨ Features

• 🤖 Multi-Agent Collaboration: Leverages CAMEL-AI and OWL frameworks for dynamic agent interactions and task automation.
• 📱 WhatsApp Integration: Access and search your personal WhatsApp messages, including media files.
• 📤 Message Dispatch: Send messages to individuals or groups directly through the app.
• 🔍 Real-Time Information Retrieval: Utilize web search capabilities for up-to-date information.
• 🌐 Streamlit Interface: Provides an intuitive UI for seamless user interaction.

🛠️ How It Works

1. Agent Roles: Defined using CAMEL-AI's RolePlaying class to simulate user and assistant interactions.
2. Toolkits Integration: Incorporates MCPToolkit for WhatsApp data access and SearchToolkit for web searches.
3. Task Execution: OWL framework orchestrates the agents to perform tasks based on user input.
4. User Interface: Streamlit app captures user tasks and displays results in real-time.

🚀 Getting Started

1. Clone the Repository:

   git clone https://github.com/Bipul70701/WhatsApp_MCP_Server.git
   cd WhatsApp_MCP_Server
   

2. Create a Virtual Environment:

   python -m venv venv
   

3. Activate the Virtual Environment:

   • On Windows:

     venv\Scripts\activate
     

   • On macOS/Linux:

     source venv/bin/activate
     

4. Install Dependencies:

   pip install -r requirements.txt
   

5. Configure Environment Variables:

   • Rename .env_template to .env.
   • Fill in the required API keys and configurations.

6. Configure MCP Server:

   • Install and Set Up WhatsApp MCP Server:
     • Follow the instructions in the WhatsApp MCP server repository to install and run the server.
     • Ensure the server is running and accessible.

7. Run the Streamlit App:

   streamlit run project.py
   

📂 Project Structure

owl-whatsapp-mcp/
├── project.py                # Main Streamlit application
├── owl/                      # OWL framework and utilities
│   └── utils/                # Utility functions and helpers
├── mcp_servers_config.json   # Configuration for MCP servers
├── requirements.txt          # List of dependencies
├── .env_template             # Example environment variables file
└── README.md                 # Project documentation

🔧 Key Components

• CAMEL-AI: Framework for designing and managing autonomous agents.
• OWL: Optimized Workforce Learning for real-time task management and collaboration.
• MCPToolkit: Facilitates interaction with WhatsApp data.
• SearchToolkit: Enables web search capabilities.
• Streamlit: Provides an interactive web interface for user interaction.

🙌 Credits

• CAMEL-AI: For the multi-agent framework.
• OWL: For real-time task management and collaboration.
• WhatsApp MCP Server: For WhatsApp data integration.
• Streamlit: For the interactive UI.

Made with ❤️ by Bipul Kumar Sharma