Microsoft Launches “Model Context Protocol (MCP) Beginner Course” – AI Tutorial

The Model Context Protocol (MCP) Beginner Course is a newly launched educational initiative by Microsoft, designed to teach the fundamentals and applications of the Model Context Protocol (MCP). This course provides a structured learning path for beginners, covering a comprehensive range of topics from core concepts and security practices to real-world development.

It is available in over 40 languages, including French, Spanish, German, Russian, Arabic, Simplified and Traditional Chinese, Japanese, and Korean. With practical code examples in multiple programming languages—such as C#, Java, JavaScript, Python, and TypeScript—the course helps developers quickly grasp MCP’s role in standardizing interactions between AI models and clients.

The curriculum includes practical modules on environment setup, testing, deployment, and community contribution, supporting learners in bridging theory and practice. It is suitable for AI developers, system architects, and software engineers.

The content of the MCP course

• 00 Introduction to MCP: An overview of the Model Context Protocol and its importance in the AI pipeline, including the significance of standardization and real-world use cases.

• 01 Core Concepts: In-depth exploration of MCP’s foundational concepts: client-server architecture, key protocol components, and messaging patterns.

• 02 MCP Security: Understanding system-level security threats and implementing protective measures using best practices and technologies.

• 03 Quick Start Guide:

  • 3.1 First Server: Build a basic MCP-compliant server and understand its interaction with clients.

  • 3.2 First Client: Set up a basic MCP client and test communication.

  • 3.3 LLM-Integrated Client: Create an MCP client that integrates with large language models (LLMs).

  • 3.4 VS Code Integration: Configure VS Code as an MCP protocol consumer.

  • 3.5 SSE-Based Server: Develop internet-exposed services using Server-Sent Events (SSE).

  • 3.6 AI Toolkit Integration: Manage AI workflows using the Microsoft AI Toolkit.

  • 3.7 Server Testing: Methodologies for server testing with various toolchains.

  • 3.8 Server Deployment: A complete guide to deploying MCP servers from development to production.

• 04 Practical Development: Cross-language SDK use, debugging, verification, and reusable prompt template development.

• 05 Advanced Topics:

  • 5.1 Azure Integration: Deep integration with Azure cloud services.

  • 5.2 Multimodal Processing: Handling images and other multimodal data.

  • 5.3 OAuth2 Authentication: Demonstration of token-based security using Spring Boot.

  • 5.4 Root Context Management: Design and implementation of context root nodes.

  • 5.5 Routing Strategies: Techniques for dynamic routing and load balancing.

  • 5.6 Sampling Mechanisms: Data sampling algorithms and performance optimization.

  • 5.7 Scalability Solutions: Horizontal/vertical scaling and resource tuning.

  • 5.8 Security Hardening: Advanced strategies for authentication, authorization, and data protection.

  • 5.9 Web Search Integration: Python server integrating real-time search via SerpAPI.

  • 5.10 Real-Time Stream Processing: Architecture for low-latency data stream handling.

• 06 Community Contributions: Guidelines and standards for contributing to the codebase and documentation.

• 07 Implementation Insights: Real-world deployment experiences and a roadmap for the future.

• 08 Best Practices: Performance tuning, fault tolerance, and resilience testing strategies.

• 09 Case Studies: Architectural blueprints and deployment schemes for typical solutions.

• 10 AI Workflow in Practice: End-to-end development of an MCP-compliant server using the Microsoft AI Toolkit.

Sample MCP Projects

Basic MCP Calculator Projects (by Language):

• C# MCP Server Example

• Java MCP Calculator App

• JavaScript MCP Demo Project

• Python MCP Server

• TypeScript MCP Example

Advanced MCP Calculator Projects:

• Advanced C# Implementation

• Java Containerized Application Example

• JavaScript Advanced Usage Sample

• Python Complex System Implementation

• TypeScript Containerized Example

Course Access

• Course Repository: https://github.com/microsoft/mcp-for-beginners/

Target Audience

• AI Developers: Ideal for developers aiming to master standardized interactions between AI models and clients, with practical multilingual code examples.

• System Architects: Helps architects understand MCP’s role in the AI pipeline and design scalable, secure AI systems.

• Software Engineers: Offers a step-by-step learning path from basic to advanced concepts for engineers with programming experience.

• AI and Programming Enthusiasts: A solid starting point for beginners interested in AI and software development, with multiple sample projects in various languages.

• Technical Professionals Expanding Skills: Aids professionals in enhancing their AI and machine learning capabilities by learning how to interact with AI models using MCP.