MCP Server (Master Control Program)

A centralized control server for managing and coordinating distributed agents and tasks.

Overview

The MCP Server provides a central coordination point for distributed agents, allowing for:

• Agent registration and monitoring
• Task creation and assignment
• Status tracking and reporting
• Secure API-based communication

This implementation is a skeletal structure that can be extended for specific use cases such as distributed computing, workflow orchestration, or agent-based systems.

Features

• Agent Management: Register, monitor, and control distributed agents
• Task Management: Create, assign, and track tasks
• API-First Design: RESTful API with FastAPI
• Authentication: API key-based authentication
• Configuration: Environment-based configuration

Getting Started

Prerequisites

• Python 3.8+
• Virtual environment (recommended)

Installation

1. Clone the repository

git clone https://github.com/yourusername/mcp-server.git
cd mcp-server

2. Create and activate a virtual environment

python -m venv venv
source venv/bin/activate  # On Windows: venvScriptsactivate

3. Install dependencies

pip install -r requirements.txt

4. Configure environment variables

cp .env.example .env
# Edit .env with your settings

Running the Server

Start the development server:

python server.py

Or using uvicorn directly:

uvicorn server:app --reload

The server will be available at http://localhost:8000. API documentation is available at http://localhost:8000/docs.

API Documentation

Once the server is running, visit http://localhost:8000/docs for Swagger UI API documentation, or http://localhost:8000/redoc for ReDoc documentation.

Key Endpoints

• GET /health - Health check endpoint
• GET /api/v1/agents - List all registered agents
• POST /api/v1/agents - Register a new agent
• GET /api/v1/tasks - List all tasks
• POST /api/v1/tasks - Create a new task
• POST /api/v1/tasks/{task_id}/assign/{agent_id} - Assign a task to an agent

Development

Project Structure

mcp-server/
├── server.py           # Main application entry point
├── config.py           # Configuration management
├── models.py           # Data models
├── routes.py           # API routes
├── requirements.txt    # Dependencies
├── .env.example        # Example environment variables
└── README.md           # Documentation

Future Enhancements

• Database integration for persistent storage
• User authentication and multi-tenancy
• WebSocket support for real-time updates
• Advanced task scheduling and prioritization
• Agent capabilities matching for task assignment
• Monitoring dashboard

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.