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Overview

Want to build your own AI-powered healthcare application? You can integrate Eka.care MCP into any application that supports the Model Context Protocol standard.

Build AI Health Apps

Create custom healthcare assistants

Automation Tools

Automate clinic workflows

Internal Tools

Custom admin dashboards

Web Services

API-powered AI services

Quick Integration

Using the MCP SDK

The easiest way is to use the official MCP SDK in your preferred language:
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client

# Create MCP client connection
server_params = StdioServerParameters(
    command="/path/to/.venv/bin/python",
    args=["-m", "eka_mcp_sdk.server"],
    env={
        "EKA_CLIENT_ID": "your_client_id",
        "EKA_CLIENT_SECRET": "your_client_secret",
        "EKA_API_KEY": "your_api_key"
    }
)

async with stdio_client(server_params) as (read, write):
    async with ClientSession(read, write) as session:
        # Initialize connection
        await session.initialize()

        # List available tools
        tools = await session.list_tools()
        print(f"Available tools: {[t.name for t in tools]}")

        # Call a tool
        result = await session.call_tool(
            "search_patients",
            arguments={"prefix": "Kumar"}
        )
        print(result)

HTTP Integration

Prefer REST APIs? Deploy the MCP server with HTTP transport:

Setup HTTP Server

server.py
from fastmcp import FastMCP
from eka_mcp_sdk.tools.patient_tools import register_patient_tools
from eka_mcp_sdk.tools.appointment_tools import register_appointment_tools

# Create FastMCP instance
mcp = FastMCP("Eka.care MCP")

# Register tools
register_patient_tools(mcp)
register_appointment_tools(mcp)

# Run with HTTP transport
if __name__ == "__main__":
    import uvicorn
    uvicorn.run(mcp.get_asgi_app(), host="0.0.0.0", port=8000)

Call via HTTP

# List available tools
curl http://localhost:8000/tools

# Call a tool
curl -X POST http://localhost:8000/call_tool \
  -H "Content-Type: application/json" \
  -d '{
    "name": "search_patients",
    "arguments": {"prefix": "Kumar"}
  }'

Docker Deployment

Deploy as a containerized service:
Dockerfile
FROM python:3.11-slim

WORKDIR /app

# Install dependencies
COPY requirements.txt .
RUN pip install -r requirements.txt

# Copy MCP server code
COPY . .

# Install package
RUN pip install -e .

# Expose port
EXPOSE 8000

# Run server
CMD ["python", "-m", "eka_mcp_sdk.server"]
docker-compose.yml
version: '3.8'

services:
  eka-mcp:
    build: .
    ports:
      - "8000:8000"
    environment:
      - EKA_CLIENT_ID=${EKA_CLIENT_ID}
      - EKA_CLIENT_SECRET=${EKA_CLIENT_SECRET}
      - EKA_API_KEY=${EKA_API_KEY}
      - EKA_API_BASE_URL=https://api.eka.care
    restart: unless-stopped

Building Something Cool? We’d love to hear about it!