Whatsapp MCP Server

🚀 OWL x WhatsApp MCP Server Integration

Welcome to the OWL x WhatsApp MCP Server project! This application integrates the WhatsApp MCP Server with the OWL Multi-Agent Framework. Through an intuitive Streamlit user interface, it enables AI agents to interact with your WhatsApp data.

🚀 Quick Start

Step 1: Clone the Repository

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

Step 2: Create a Virtual Environment

python -m venv venv

Step 3: Activate the Virtual Environment

• Windows:

venv\Scripts\activate

• macOS/Linux:

source venv/bin/activate

Step 4: Install Dependencies

pip install -r requirements.txt

Step 5: Configure Environment Variables

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

Step 6: Configure the MCP Server

• Install and Set Up the 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.

Step 7: Run the Streamlit Application

streamlit run project.py

✨ Features

• 🤖 Multi-Agent Collaboration: Utilize the CAMEL-AI and OWL frameworks to enable dynamic agent interactions and task automation.
• 📱 WhatsApp Integration: Access and search personal WhatsApp messages, including media files.
• 📤 Message Sending: Send messages directly to individuals or groups through the application.
• 🔍 Real-Time Information Retrieval: Use the web search function to obtain the latest information.
• 🌐 Streamlit Interface: Provide an intuitive user interface for seamless interaction.

🛠️ How It Works

1. Agent Role Definition: Use the RolePlaying class of CAMEL-AI to simulate interactions between users and assistants.
2. Toolkit Integration: Integrate the MCPToolkit for WhatsApp data access and the SearchToolkit for web search.
3. Task Execution: The OWL framework coordinates agents to complete tasks based on user input.
4. User Interface: The Streamlit application captures user tasks and displays results in real-time.

📂 Project Structure

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

🔧 Key Components

• CAMEL-AI: A framework for designing and managing autonomous agents.
• OWL: Optimized workflow learning for real-time task management and collaboration.
• MCPToolkit: Facilitates interaction with WhatsApp data.
• SearchToolkit: Enables web search functionality.
• Streamlit: Provides an interactive web interface for user interaction.

🙌 Acknowledgments

• CAMEL-AI: Multi-agent framework.
• OWL: Real-time task management and collaboration.
• WhatsApp MCP Server: Integration for WhatsApp data.
• Streamlit: For building interactive user interfaces.

Thank you for your interest in the OWL x WhatsApp MCP Server project! If you have any questions or suggestions, please feel free to contact us.