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MCP Server Basic Example

by krishnaik06

MCP Server Basic Example

This is a basic example of a Model Context Protocol (MCP) server implementation that demonstrates core functionality including tools and resources.

Setup Steps

  1. Initialize the project (Go to any local folder and launch powershell or cmd):
uv init mcp-server-basic cd mcp-server-basic
  1. Create virtual environment and activate it

uv venv .venv\Scripts\activate
  1. Install dependencies:
uv add "mcp[cli]"

or

uv add -r requirements.txt

Features

The server implements the following features:

Tools

  • add(a: int, b: int): Adds two numbers
  • subtract(a: int, b: int): Subtracts second number from first

Resources

  • greeting://{name}: Returns a personalized greeting

Running the Server

To run the server with the MCP Inspector for development:

uv run mcp dev main.py

To run the server normally:

uv run mcp run

To install the server in Claude desktop app:

uv run mcp install main.py

MCP connect in VS code

  • Open folder/mcp-server-basic in vs code
  • open terminal and run below command :
uv run main.py
  • Click Cntrl+Shift+I to launch chat in vs code
  • Do login with Github and setup
  • Folow the below steps (two way to add mcp configuration for vs code user settings):

Watch the demo

Project Structure

  • main.py: Main server implementation with tools and resources
  • pyproject.toml: Project configuration and dependencies

2.0 Agentic AI And GENERATIVE AI With MCP Bootcamp

image

Enroll Now

Course Overview:

Mentors: Sourangshu Paul, Mayank Aggarwal , Krish And Sunny

Start Date 10th 2025

Timing: 8am to 11am IST(Saturday And Sunday)

Duration : 4-5 months

This course is designed for AI developers, machine learning engineers, data scientists, and software engineers looking to build expertise in agentic AI, multi-agent systems, and AI-powered automation. Whether you are new to AI agents or have experience in NLP and GenAI, this course will equip you with the knowledge and hands-on skills required to develop, deploy, and manage AI agents at scale. By the end of the course, you will have a strong foundation in agentic AI frameworks, multi-agent collaboration, real-world automation, and end-to-end AI deployment, along with practical experience through real-world projects.

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security - not tested
A
license - permissive license
-
quality - not tested

A simple implementation of a Model Context Protocol server that demonstrates core functionality including mathematical tools (add, subtract) and personalized greeting resources.

  1. Setup Steps
    1. Create virtual environment and activate it
      1. Features
      2. Running the Server
      3. MCP connect in VS code
      4. Project Structure
      5. 2.0 Agentic AI And GENERATIVE AI With MCP Bootcamp

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