Medical Appointment Assistant

Example Use Cases

• 1

  Detect user intent and extract appointment details from natural language queries.

• 2

  Securely manage medical appointment data with controlled access and JSON persistence.

• 3

  A reliable backend orchestration layer separating AI NLP tasks from business logic.

Description

This backend server uses a Model Context Protocol (MCP) design pattern to separate intent detection, NLP tasks, and business logic for managing medical appointments. It leverages Groq's hosted LLaMA-3.1 model for natural language understanding and entity extraction, while all appointment CRUD operations and data persistence are handled securely by dedicated services. The architecture ensures safety, reliability, and clear separation of concerns, making it suitable for production-ready AI medical assistants.