🧠 MCP-Powered AI Learning Path Generator

A student-friendly project demonstrating how an AI learning application can use the Model Context Protocol (MCP) to call structured tools.

Current architecture

User
  ↓
Streamlit Web App
  ↓
MCP Client
  ↓
MCP Server
  ├── generate_learning_path
  └── find_learning_resources
  ↓
Personalized Learning Path

Related MCP server: Learning Coach MCP Server

Features

• Learning topic, duration and level input

• Day-by-day roadmap

• Concepts and practice tasks

• Project ideas

• Learning resource links

• JSON download

• Real MCP client → MCP server tool calls

Run locally

Python 3.10+ is required.

python -m venv .venv

Windows:

.venv\Scripts\activate

Install:

pip install -r requirements.txt

Run:

streamlit run app.py

MCP inspection

The official MCP Python SDK provides development tooling. You can inspect the server separately with:

mcp dev mcp_server.py

Next integration stage

For the workshop submission, this starter can be extended with real external services:

• YouTube search/API tool

• Google Drive document creation

• Notion page creation

• Optional LLM-generated personalization

Keep credentials in environment variables or Streamlit secrets. Never commit real API keys.

Project purpose

This is not just a chatbot. The application demonstrates the MCP pattern:

AI/application → MCP client → MCP server → tools → structured results

License

For educational/project use.