MCP-Clinic-Bot

Overview

MCP-Clinic-Bot is a comprehensive medical chatbot solution built on Model Context Protocol. It integrates Google Gemini AI for conversational intelligence with ChromaDB for semantic search of clinic information. The system provides appointment management capabilities through a responsive React interface, with Node.js and MongoDB handling backend operations. MCP tools enable structured interactions for creating, checking, updating, and deleting appointments, as well as retrieving clinic information through vector search.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

• createAppointment

  Book new appointments for medical services

  Try:I'd like to book an appointment for tomorrow at 2 PMTry:Can I schedule a checkup with Dr. Smith next week?
• checkForAppointments

  View existing appointments for a patient

  Try:Do I have any appointments this week?Try:Show me my upcoming medical appointments
• updateAppointment

  Modify existing appointment details

  Try:I need to change my appointment time to 3 PM instead of 2 PMTry:Can I update my appointment to a different doctor?
• deleteAppointment

  Cancel or remove existing appointments

  Try:I need to cancel my appointment next TuesdayTry:Please delete my appointment with Dr. Johnson
• ClinicInfo

  Retrieve clinic information using vector search

  Try:What services do you provide?Try:Tell me about your clinic hours and locationTry:Do you offer pediatric care?

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Installation

cd backend
npm install

GEMINI_API_KEY=your_gemini_api_key
MONGODB_URI=mongodb://localhost:27017/clinic_chatbot
PORT=5000

cd frontend/mcp_chatbot
npm install

cd backend
npm run dev

cd frontend/mcp_chatbot
npm run dev

cd backend
npm run inspector

{
  "mcpServers": {
    "clinic-bot": {
      "command": "node",
      "args": ["backend/mcpServer.js"]
    }
  }
}

FAQ

Can this chatbot be customized for different medical specialties?

Yes, the system can be extended to support different specialties by updating the ChromaDB vector store with specialty-specific information and modifying MCP tools accordingly.

What security measures are in place for patient data?

The application stores appointment data in MongoDB and uses environment variables for API keys. However, no additional security measures like encryption are explicitly mentioned in the documentation.

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