MCP (Multi-Context Processing) Simulation

Overview

I've developed this Multi-Context Processing (MCP) system to handle and process multiple contexts efficiently. The project simulates a robust architecture for managing complex data processing tasks with a focus on scalability and maintainability.

Features

• Multi-context data processing
• Database integration for persistent storage
• Modular architecture for easy extension
• Video demonstration available in the public folder
• Comprehensive architecture documentation

System Architecture

Getting Started

Prerequisites

• Python 3.x
• Virtual environment (recommended)

Installation

1. Clone the repository
2. Create and activate a virtual environment:

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

3. Install dependencies:

   pip install -r requirements.txt
   

4. Initialize the database:

   python setup_db.py
   

Running the Application

python main.py

Documentation

• Check out the architecture diagram above for a detailed view of the system design
• Watch the demo video to see the system in action

Technical Details

The project implements a sophisticated multi-context processing system that:

• Manages multiple data contexts simultaneously
• Provides efficient data persistence through SQLite
• Implements modular design patterns for maintainability
• Offers clear separation of concerns between data, logic, and presentation layers

Contributing

Feel free to submit issues and enhancement requests!