mcp-for-beginners

🥇Gold

Explore the fundamentals of Model Context Protocol (MCP) with this open-source curriculum. It provides practical, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust, and Python, empowering developers to create modular and secure AI workflows.

14,4794,6650Updated Today

Beginner15 minutes to implementdevelopment

Saves ~75 min per use

Quick InstallView Source

claude install microsoft/mcp-for-beginners

Works with:

GitHub CopilotVS Code

Overview

About This Skill

Use Cases

Build modular AI applications that can be easily maintained and updated.

Create secure AI services that protect sensitive data and ensure compliance.

Orchestrate AI workflows that integrate multiple services and languages.

Implement cross-language solutions that allow seamless interaction between different programming environments.

Best For

GrowthRevOps

Setup & Installation

Quick Install

Terminal

claude install microsoft/mcp-for-beginners

Alternative Install (Git Clone)

git clone https://github.com/microsoft/mcp-for-beginners

Requirements

Claude Code or compatible AI agent
Works with: GitHub Copilot, VS Code

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I want to learn about the Model Context Protocol (MCP) for [COMPANY] in the [INDUSTRY] industry. Can you provide a brief overview of its fundamentals and practical applications, including examples in [LANGUAGE]?

Example Output

### Overview of Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a framework designed to enhance the modularity and security of AI workflows. It allows developers to create reusable components that can communicate effectively across different programming languages.

### Practical Applications
- **Cross-Language Compatibility**: MCP supports .NET, Java, TypeScript, JavaScript, Rust, and Python, making it versatile for various development environments.
- **Modular Design**: By using MCP, developers can break down complex AI systems into manageable modules, improving maintainability.

### Example Usage in Python
```python
# Example of a simple MCP implementation in Python
class ModelContext:
    def __init__(self, model_name):
        self.model_name = model_name

    def run(self, data):
        # Process data with the specified model
        return f'Processed {data} with {self.model_name}'

context = ModelContext('MyModel')
result = context.run('sample data')
print(result)  # Output: Processed sample data with MyModel
```