metadata

title: Model Context Protocol (MCP) example
emoji: 📋
colorFrom: blue
colorTo: purple
sdk: docker
sdk_version: '3.11'
app_file: mcp_task_client.py
pinned: false
license: mit
short_description: MCP Task Manager CLI

Model Context Protocol (MCP) Example Implementation

This repository demonstrates the implementation of the Model Context Protocol (MCP), a standardized approach for managing context in AI/ML models.

To get more details, look at the post How to create an MCP server and client with an LLM

Overview

MCP (Model Context Protocol) is a protocol designed to standardize how context is handled when working with AI/ML models. This example repository shows how to implement and use MCP in your projects.

Getting Started

Prerequisites

Python 3.8 or higher
pip (Python package installer)

Setup Virtual Environment

Windows

First, open Command Prompt and follow these steps:

Create and navigate to your project directory:

cd mcp_example

Create a virtual environment:

python -m venv app

Activate the virtual environment:

venv\Scripts\activate

Your prompt should now show "(venv)" at the beginning, indicating the virtual environment is active.
Install required packages:

pip install -r requirements.txt

macOS

Open Terminal and follow these steps:

Create and navigate to your project directory:

mkdir mcp_example
cd mcp_example

Create a virtual environment:

python3 -m venv venv

Activate the virtual environment:

source venv/bin/activate

Your prompt should now show "(venv)" at the beginning, indicating the virtual environment is active.
Install required packages:

pip install -r requirements.txt