MCP Slack Python

Developer tools Artificial intelligence chatbots .Python

rating : 2 points

downloads : 6

update time : 2025-04-28

What is MCP Demo?

MCP Demo is a project that showcases the functions of the Model Control Protocol. It provides a basic framework and tools for interacting with AI models. This project is suitable for developers to quickly understand and use the MCP protocol.

How to use MCP Demo?

Through simple installation steps and configuration, you can run MCP Demo to test and experience the functions of the Model Control Protocol. The project provides a complete test suite and sample code.

Applicable scenarios

Suitable for scenarios such as AI model development, testing MCP protocol functions, and learning the implementation of the model control protocol.

Main features

MCP protocol implementationComplete basic implementation of the Model Control Protocol

Test suiteContains a complete set of test cases to verify MCP functions

Environment configurationSupports configuring environment variables through the.env file

Advantages and limitations

Advantages

Quickly get started and experience the MCP protocol

Complete test coverage

Modern Python project structure

Limitations

Only basic demonstration functions

Requires a Python development environment

Documentation is mainly technical documentation

How to use

Clone the repository

Clone the project code to the local machine

Install uv

Install the uv tool for virtual environment and dependency management

Create a virtual environment

Use uv to create a Python virtual environment

Install dependencies

Use uv to install project dependencies

Configure environment variables

Copy and modify the environment variable configuration file

🚀 MCP Demo Project

This repository contains the implementation of the MCP (Model Control Protocol) demo project, which provides a practical demonstration of the MCP's capabilities.

🚀 Quick Start

Prerequisites

Ensure you have uv installed. If not, you can install it by running the following command:

curl -LsSf https://astral.sh/uv/install.sh | sh

Steps

Clone the repository:

git clone <repository-url>
cd mcp-demo

Create and activate a virtual environment using uv:

uv venv
source .venv/bin/activate  # On Unix/macOS systems
# Or
.venv\Scripts\activate     # On Windows

Install the dependencies using uv:

uv pip install -e .

Configure the environment variables:

cp .env.example .env
# Edit the .env file as needed

Run the main application:

python main.py

Running Tests

To run the test suite, use the following command:

pytest

✨ Features

This project showcases the implementation of the MCP through a practical application, demonstrating its core features and usage scenarios.

📦 Installation

Clone the Repository

git clone <repository-url>
cd mcp-demo

Install `uv`

curl -LsSf https://astral.sh/uv/install.sh | sh

Create and Activate a Virtual Environment

uv venv
source .venv/bin/activate  # On Unix/macOS systems
# Or
.venv\Scripts\activate     # On Windows

Install Dependencies

uv pip install -e .

Configure Environment Variables

cp .env.example .env
# Edit the .env file as needed

💻 Usage Examples

Basic Usage

To start the application, follow these steps:

Activate the virtual environment:

source .venv/bin/activate  # On Unix/macOS systems
# Or
.venv\Scripts\activate     # On Windows

Run the main application:

python main.py

📚 Documentation

Project Structure

mcp-demo/
├── main.py         # Main entry point of the application
├── tools/          # Tools and helper functions
├── tests/          # Test suite
├── .env           # Environment variables (not tracked in Git)
└── pyproject.toml  # Project dependencies and configuration