AI-Powered Todo Application

A modern todo application with AI integration built using React, Node.js, Express, MongoDB, and Docker.

Features

• Create, read, update, and delete todos
• AI-powered todo suggestions
• Priority-based todo organization
• Due date tracking
• Completed task management
• Docker-based deployment

Tech Stack

• Frontend: React.js with Material-UI
• Backend: Node.js with Express
• Database: MongoDB
• AI Integration: Ollama for AI suggestions
• Containerization: Docker and Docker Compose

Project Structure

.
├── client/                 # Frontend React application
├── services/              # Backend services
│   └── mcpService.js     # Main service for todo operations
├── models/               # Database models
│   └── Todo.js          # Todo model definition
├── server.js             # Main Express server
├── docker-compose.yml    # Docker configuration
├── Dockerfile           # Backend Docker configuration
└── package.json         # Project dependencies

Prerequisites

• Node.js (v18 or higher)
• Docker and Docker Compose
• MongoDB
• Ollama (for AI suggestions)

Installation

1. Clone the repository:

git clone https://github.com/jeshu/ai-todo-app.git
cd ai-todo-app

2. Install dependencies:

# Install backend dependencies
npm install

# Install frontend dependencies
cd client
npm install

3. Set up environment variables: Create a .env file in the root directory with:

MONGODB_URI=mongodb://localhost:27017/mcp-todo-app
PORT=5001

4. Start the application:

docker-compose up -d

Running the Application

The application will be available at:

• Frontend: http://localhost:3000
• Backend API: http://localhost:5001

API Endpoints

• GET /api/todos - Get all todos
• POST /api/todos - Create a new todo
• PUT /api/todos/:id/toggle - Toggle todo completion
• DELETE /api/todos/:id - Delete a todo
• POST /api/ai/suggestions - Get AI suggestions
• POST /api/ai/analyze - Analyze todo list
• POST /api/ai/schedule - Schedule todos

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

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