Custom MCP Client

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:

Python
TypeScript
Go

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)

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";

const transport = new StdioClientTransport({
  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"
  }
});

const client = new Client({
  name: "my-healthcare-app",
  version: "1.0.0"
}, {
  capabilities: {}
});

await client.connect(transport);

// List available tools
const tools = await client.listTools();
console.log("Available tools:", tools.tools.map(t => t.name));

// Call a tool
const result = await client.callTool({
  name: "search_patients",
  arguments: { prefix: "Kumar" }
});
console.log(result);

package main

import (
    "context"
    "fmt"
    "github.com/modelcontextprotocol/sdk-go/client"
)

func main() {
    // Create MCP client
    c := client.NewStdioClient(
        "/path/to/.venv/bin/python",
        []string{"-m", "eka_mcp_sdk.server"},
        map[string]string{
            "EKA_CLIENT_ID":     "your_client_id",
            "EKA_CLIENT_SECRET": "your_client_secret",
            "EKA_API_KEY":       "your_api_key",
        },
    )

    // Connect
    ctx := context.Background()
    if err := c.Connect(ctx); err != nil {
        panic(err)
    }
    defer c.Close()

    // List tools
    tools, err := c.ListTools(ctx)
    if err != nil {
        panic(err)
    }
    fmt.Printf("Available tools: %+v\n", tools)

    // Call a tool
    result, err := c.CallTool(ctx, "search_patients", map[string]interface{}{
        "prefix": "Kumar",
    })
    if err != nil {
        panic(err)
    }
    fmt.Printf("Result: %+v\n", 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!

Email us: ekaconnect@eka.care
Get featured in our showcase!

Eka Overview

Product Details

Overview

📱 Build AI Health Apps

🤖 Automation Tools

🔧 Internal Tools

🌐 Web Services

Quick Integration

Using the MCP SDK

HTTP Integration

Setup HTTP Server

Call via HTTP

Docker Deployment

​Overview

📱 Build AI Health Apps

🤖 Automation Tools

🔧 Internal Tools

🌐 Web Services

​Quick Integration

​Using the MCP SDK

​HTTP Integration

​Setup HTTP Server

​Call via HTTP

​Docker Deployment

Overview

Quick Integration

Using the MCP SDK

HTTP Integration

Setup HTTP Server

Call via HTTP

Docker Deployment