Learning Path Generator with Model Context Protocol (MCP)

This project is a Streamlit-based web application that generates personalized learning paths using the Model Context Protocol (MCP). It integrates with various services including YouTube, Google Drive, and Notion to create comprehensive learning experiences.

Features

• 🎯 Generate personalized learning paths based on your goals
• 🎥 Integration with YouTube for video content
• 📁 Google Drive integration for document storage
• 📝 Notion integration for note-taking and organization
• 🚀 Real-time progress tracking
• 🎨 User-friendly Streamlit interface

Prerequisites

• Python 3.10+
• Google AI Studio API Key
• Hugging Face API Key
• Composio API Key (for direct MCP integration)

Installation

1. Clone the repository:

2. Create and activate a virtual environment:

3. Install the required packages:

pip install -r requirements.txt

Configuration

1. Create .env file

Copy .env.example to .env and add your API keys:

GOOGLE_API_KEY=your_google_ai_studio_key
HF_API_KEY=your_huggingface_key
COMPOSIO_API_KEY=your_composio_api_key

Get API Keys:

• Google AI Studio: https://makersuite.google.com/app/apikey
• Hugging Face: https://huggingface.co/settings/tokens
• Composio: https://app.composio.dev/settings

2. Connect Composio Integrations

Connect the apps you want to use:

composio add youtube           # Required
composio add googledrive       # Optional
composio add notion            # Optional

See COMPOSIO_DIRECT_SETUP.md for detailed setup instructions.

Running the Application

To start the application, run:

streamlit run app.py

The application will be available at http://localhost:8501 by default.

Usage

1. Ensure your .env file has all required API keys
2. Make sure Composio integrations are connected (see Configuration above)
3. In the Streamlit app sidebar:
   • Select AI model(s) for comparison
   • Choose secondary tool: None, Drive, or Notion
4. Enter your learning goal (e.g., "I want to learn python basics in 3 days")
5. Click "Generate Learning Path" to create your personalized learning plan

Note: YouTube integration is always enabled. Drive and Notion are optional.

Project Structure

• app.py - Main Streamlit application
• utils.py - Utility functions and helper methods
• prompt.py - Prompt template
• requirements.txt - Project dependencies