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JAYAKRISHNA-AI-ENGINEER

MCP Demo Server

by JAYAKRISHNA-AI-ENGINEER
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Python
Local

MCP Demo Project

Overview

This project demonstrates how to build and test a Model Context Protocol (MCP) server using Python and FastMCP.

The repository contains:

  • server.py - MCP Server implemented using FastMCP

  • server.js - Sample REST API implemented using Express.js

  • client_test.py - Python client for testing the MCP server

  • requirements.txt - Python dependencies

  • package.json - Node.js dependencies (optional)

Architecture

+----------------------+
| MCP Client           |
| (Claude, Cursor,     |
|  Custom Client)      |
+----------+-----------+
           |
           | MCP Protocol
           |
           v
+----------------------+
| server.py            |
| FastMCP Server       |
+----------+-----------+
           |
           | HTTP (Optional)
           |
           v
+----------------------+
| server.js            |
| Express REST API     |
+----------+-----------+
           |
           v
+----------------------+
| Database / Services  |
+----------------------+

The MCP server exposes tools, resources, and prompts that AI agents can use.

The Express server demonstrates how an MCP server can interact with existing REST APIs.

Services

Related MCP server: Simple FastMCP Server

1. Python MCP Server (server.py)

The MCP server runs on:

http://127.0.0.1:8000/mcp

Available Tools

add_numbers

Adds two integers.

Example:

{
  "a": 5,
  "b": 7
}

Result:

12

get_weather

Returns mock weather information.

Example:

{
  "city": "Hyderabad"
}

Result:

The weather in Hyderabad is sunny, 25°C.

Available Resources

greeting://{name}

Example:

greeting://Jaya

Result:

Hello, Jaya! Welcome to MCP.

Available Prompts

code_review_prompt

Generates a code review prompt.

Input:

public class Test {}

Output:

Please review this code and suggest improvements:

public class Test {}

2. Node.js REST Server (server.js)

The Express server runs on:

http://localhost:3000

Endpoints

Health Check

GET /health

Example Response:

{
  "status": "ok",
  "uptime": 123.45
}

Manifest

GET /manifest

Returns server metadata.

Context API

POST /context

Request:

{
  "query": "Hello MCP",
  "metadata": {
    "user": "Jaya"
  }
}

Response:

{
  "received": {
    "query": "Hello MCP",
    "metadata": {
      "user": "Jaya"
    }
  },
  "response": "MCP server received: Hello MCP"
}

Prerequisites

Python

Verify installation:

python --version

Install dependencies:

pip install -r requirements.txt

Node.js (Optional)

Verify installation:

node -v
npm -v

Install dependencies:

npm install

or

npm install express

Running the Application

Start the MCP Server

python server.py

Expected Output:

Uvicorn running on http://127.0.0.1:8000

Start the Express Server

node server.js

Expected Output:

MCP server listening on http://localhost:3000

Testing the MCP Server

Step 1: Initialize Session

Windows CMD:

curl -v -H "Accept: application/json, text/event-stream" -H "Content-Type: application/json" http://127.0.0.1:8000/mcp -d "{\"jsonrpc\":\"2.0\",\"id\":\"1\",\"method\":\"initialize\",\"params\":{\"protocolVersion\":\"2025-03-26\",\"capabilities\":{},\"clientInfo\":{\"name\":\"curl\",\"version\":\"1.0\"}}}"

Copy the returned:

mcp-session-id

Step 2: List Available Tools

curl -v -H "Accept: application/json, text/event-stream" -H "Content-Type: application/json" -H "Mcp-Session-Id: <SESSION_ID>" http://127.0.0.1:8000/mcp -d "{\"jsonrpc\":\"2.0\",\"id\":\"2\",\"method\":\"tools/list\"}"

Step 3: Call add_numbers Tool

curl -v -H "Accept: application/json, text/event-stream" -H "Content-Type: application/json" -H "Mcp-Session-Id: <SESSION_ID>" http://127.0.0.1:8000/mcp -d "{\"jsonrpc\":\"2.0\",\"id\":\"3\",\"method\":\"tools/call\",\"params\":{\"name\":\"add_numbers\",\"arguments\":{\"a\":5,\"b\":7}}}"

Expected Result:

12

Step 4: Call get_weather Tool

curl -v -H "Accept: application/json, text/event-stream" -H "Content-Type: application/json" -H "Mcp-Session-Id: <SESSION_ID>" http://127.0.0.1:8000/mcp -d "{\"jsonrpc\":\"2.0\",\"id\":\"4\",\"method\":\"tools/call\",\"params\":{\"name\":\"get_weather\",\"arguments\":{\"city\":\"Hyderabad\"}}}"

Testing the Express Server

Health Check:

curl http://localhost:3000/health

Manifest:

curl http://localhost:3000/manifest

Context API:

curl -X POST http://localhost:3000/context -H "Content-Type: application/json" -d "{\"query\":\"Hello MCP\"}"

MCP Concepts Used

Tool

An executable function exposed to MCP clients.

Examples:

  • add_numbers

  • get_weather

Resource

Read-only contextual information.

Example:

  • greeting://{name}

Prompt

Reusable prompt templates exposed to AI clients.

Example:

  • code_review_prompt

Learning Objectives

This project demonstrates:

  • Building an MCP Server with FastMCP

  • Exposing Tools, Resources, and Prompts

  • Using Streamable HTTP Transport

  • Testing MCP APIs with curl

  • Creating a REST API with Express.js

  • Integrating MCP with existing backend services

  • Understanding MCP architecture and workflows

This server cannot be installed

F
license - not found
-
quality - not tested
C
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

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