EDUMCP is an Educational Model Context Protocol server that exposes a FastAPI-based API gateway and a collection of microservices for educational AI workflows. It enables interoperation between AI tutoring components, content generation modules, quizzes, multi-language resources, and analytics services. You can use the API gateway at http://localhost:8000 to access services such as story generation, quizzes, multimedia content assembly, and user management. The local development setup runs the user service (FastAPI) via Uvicorn, with a PostgreSQL database, MongoDB for storage, and Redis/Elasticsearch for caching and search capabilities. This MCP server structure allows diverse AI models and educational tools to share context, enabling richer and more personalized learning experiences.

Key capabilities include:

• Personalised Story Generation and Educational Content Creation
• Educational Quiz Creation and assessment tooling
• Multimedia Integration (text, images, voice, video) and language localization
• User Management with roles (parent, teacher, admin) and Parental Controls
• Asynchronous processing for long-running AI tasks to improve responsiveness
• A microservice architecture with an API Gateway coordinating dedicated services

To use the tools, start the server (as described in installation) and call the corresponding endpoints under the API Gateway, for example the text/story endpoints and the task management endpoints. The system is designed to allow other educational AI models and applications to connect through standardized MCP contexts, enabling interoperable workflows across tutoring, games, experiments, and content generation modules.

Prerequisites:

• Docker and Docker Compose (for quick setup)
• Python 3.10 or higher (for local development)

Install and run with Docker (recommended for quick startup):

1. Clone the repository: git clone https://github.com/CHILDEDUAI/aichildedu.git cd aichildedu

2. Start services with Docker Compose: docker-compose up -d

3. API Gateway will be available at: http://localhost:8000

Local development setup (Python/uvicorn):

1. Create and activate a virtual environment: python -m venv venv

   On Windows: venv\Scripts\activate

   On Unix/macOS: source venv/bin/activate

2. Install dependencies: pip install -r requirements.txt

3. Run the FastAPI/Uvicorn server (user service by default): uvicorn aichildedu.user_service.main:app --reload --port 8001

4. Access the API: API Gateway: http://localhost:8000 User Service: http://localhost:8001

Notes:

• Ensure environment variables for database connections are set (see .env in the project root if provided).
• For production, use a production-ready ASGI server setup and configure TLS/security as appropriate.

Tips and common considerations:

• Ensure PostgreSQL, MongoDB, and Redis are reachable at the configured URIs (adjust in your environment or docker-compose file).
• The SECRET_KEY should be a strong random value in production.
• If you use Docker, you can customize the docker-compose.yml to suit your deployment (scaling, traffic, or resource limits).
• The API Gateway exposes endpoints for story generation, quizzes, content retrieval, and user management; consult the API docs at http://localhost:8000/docs for details.
• If you encounter port conflicts, adjust the --port flag in the uvicorn command or modify docker-compose mappings accordingly.