Healthcare
Builds natural language interfaces for database operations using NestJS, MongoDB, and OpenAI, demonstrating Model Context Protocol for conversational AI with RAG integration and automated task execution.
Acerca de
This learning project showcases the application of the Model Context Protocol (MCP) to develop conversational AI interfaces that simplify complex technical operations. It enables users to interact with databases and systems using natural language chat, streamlining tasks like appointment management, therapist discovery, and patient data retrieval. By leveraging AI agents, Retrieval Augmented Generation (RAG), and a robust NestJS backend with MongoDB, the project demonstrates how to build intuitive systems that reduce the need for specialized technical knowledge, significantly enhancing user experience and productivity in domains like healthcare.
Características Principales
- AI-Powered Conversational Interface for healthcare operations
- Automated Database Operations via Natural Language commands
- Retrieval Augmented Generation (RAG) for Contextual AI Responses
- JWT-based Authentication System with secure user management
- Comprehensive Appointment, Patient, and Therapist Management
- 0 GitHub stars
Casos de Uso
- Automating appointment scheduling and cancellation with AI agents
- Simplifying healthcare database interactions through conversational chat
- Providing intelligent, context-aware responses for user queries in a healthcare context
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