# Educational Tutor
An experimental system that transforms documentation repositories into interactive educational content using AI and the Model Context Protocol (MCP).
## š Overview
This project consists of two main components:
1. **š Course Content Agent** - Generates structured learning courses from documentation repositories
2. **š§ MCP Educational Server** - Provides standardized access to course content via MCP protocol
## šļø Architecture
```
Documentation Repository ā Course Content Agent ā Structured Courses ā MCP Server ā AI Tutors
```
The system processes documentation, creates educational content, and exposes it through standardized tools for AI tutoring applications.
## š Project Structure
```
tutor/
āāā course_content_agent/ # AI-powered course generation from docs
ā āāā main.py # CourseBuilder orchestration
ā āāā modules.py # Core processing logic
ā āāā models.py # Pydantic data models
ā āāā signatures.py # DSPy LLM signatures
ā āāā about.md # š Detailed documentation
āāā mcp_server/ # MCP protocol server for course access
ā āāā main.py # MCP server startup
ā āāā tools.py # Course interaction tools
ā āāā course_management.py # Content processing
ā āāā about.md # š Detailed documentation
āāā course_output/ # Generated course content
āāā nbs/ # Jupyter notebooks for development
āāā pyproject.toml # Project configuration
```
## š Quick Start
### 1. Install Dependencies and Create Virtual Environment
This project uses `uv` for fast Python package management.
```bash
# Create a virtual environment
python -m uv venv
# Install dependencies in editable mode
.venv/bin/uv pip install -e .
```
### 2. Generate Courses from Documentation
```bash
# Generate courses from a repository
.venv/bin/uv run python course_content_agent/test.py
```
**Customize for Your Repository**: Edit `course_content_agent/test.py` to change:
- Repository URL (currently uses MCP docs)
- Include/exclude specific folders
- Output directory and caching settings
### 3. Start MCP Server
```bash
# Serve generated courses via MCP protocol
.venv/bin/uv run python -m mcp_server.main
# Or customize course directory
COURSE_DIR=your_course_output .venv/bin/uv run python -m mcp_server.main
```
### 4. Test MCP Integration
```bash
# Test server capabilities
.venv/bin/uv run python mcp_server/stdio_client.py
```
## š Detailed Documentation
For comprehensive information about each component:
- **Course Content Agent**: See [`course_content_agent/about.md`](course_content_agent/about.md)
- AI-powered course generation
- DSPy signatures and multiprocessing
- Document analysis and learning path creation
- **MCP Educational Server**: See [`mcp_server/about.md`](mcp_server/about.md)
- MCP protocol implementation
- Course interaction tools
- Integration with AI assistants
## š MCP Integration with Cursor
To use the educational tutor MCP server with Cursor, create a `.cursor/mcp.json` file in your project root:
```json
{
"mcpServers": {
"educational-tutor": {
"command": "/path/to/tutor/project/.venv/bin/uv",
"args": [
"--directory",
"/path/to/tutor/project",
"run",
"mcp_server/main.py"
],
"env": {
"COURSE_DIR": "/path/to/tutor/project/course_output"
}
}
}
}
```
**Setup Steps**:
1. Create a virtual environment: `python -m uv venv`
2. Install dependencies: `.venv/bin/uv pip install -e .`
3. Update the `command` path and the path in `args` to your project directory.
4. Restart Cursor or reload the window.
5. Use `@educational-tutor` in Cursor chat to access course tools.
## š§ Development Status
**Current Status**: ā
Functional MVP
- Course generation from documentation repositories
- MCP server for standardized content access
- Multi-complexity course creation (beginner/intermediate/advanced)
**Future Enhancements**:
- Support for diverse content sources (websites, videos)
- Advanced search and recommendation systems
- Integration with popular AI platforms
## š ļø Technology Stack
- **AI Framework**: DSPy for LLM orchestration
- **Content Processing**: Multiprocessing for performance
- **Protocol**: Model Context Protocol (MCP) for standardization
- **Models**: Gemini 2.5 Flash for content generation
- **Data**: Pydantic models for type safety
## š License
This project is experimental and intended for educational and research purposes.
