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Microsoft Open Source Curriculum

Model Context Protocol for Beginners

A structured, 12-module curriculum that takes you from MCP fundamentals to production-ready AI integrations — with real code examples in C#, Java, TypeScript, JavaScript, Rust, and Python.

12 Modules

Structured learning from fundamentals to advanced production patterns

6 Languages

Complete examples in C#, Java, TypeScript, JavaScript, Rust, and Python

13 Hands-On Labs

Build a production MCP server with PostgreSQL integration end-to-end

What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI models communicate with external tools and services in a unified, secure way. Think of it as USB for AI — a universal connector that allows any AI application to plug into any tool or data source without custom integration code. MCP defines a client-server architecture where:
  • MCP Hosts (Claude Desktop, VS Code, IDEs) initiate connections
  • MCP Clients maintain protocol connections within the host
  • MCP Servers expose tools, resources, and prompts to AI models
This curriculum is aligned with MCP Specification 2025-11-25 — the latest stable release. MCP uses date-based versioning (YYYY-MM-DD) for clear protocol version tracking.

Your Learning Path

Foundation (Modules 0–2)

Learn what MCP is, explore core concepts, and understand security principles before writing a single line of code.

Building Phase (Module 3)

Create your first MCP server and client, integrate with VS Code, implement auth, and test your implementations.

Practical & Advanced (Modules 4–5)

Dive into SDKs, debugging, pagination, Azure integration, OAuth2, real-time streaming, and enterprise scaling.

Mastery Phase (Modules 6–11)

Contribute to the ecosystem, study real-world case studies, and complete the 13-lab database integration capstone.

Complete Curriculum

ModuleTopicDescription
00Introduction to MCPWhat MCP is and why it matters for AI development
01Core ConceptsArchitecture, hosts, clients, servers, transports
02Security in MCPThreats, best practices, and security controls
03Getting StartedEnvironment setup, first server, first client
04Practical ImplementationSDKs, debugging, testing, prompt templates
05Advanced TopicsMulti-modal AI, scaling, enterprise deployment
06Community ContributionsContributing to the MCP ecosystem
07Early Adoption InsightsReal-world implementation stories
08Best PracticesPerformance, fault-tolerance, resilience
09Case StudiesPractical implementation examples
10AI Toolkit WorkshopBuilding MCP servers with AI Toolkit
11Hands-On Labs13-lab PostgreSQL integration capstone

Hands-On Labs

The MCP Server Hands-On Labs are a comprehensive 13-lab series that teaches you to build a production-ready MCP server with PostgreSQL integration, semantic search, Azure deployment, and monitoring.

Start the Labs

Begin the 13-lab series to build a full production MCP server

View Code Samples

Browse working code examples in all 6 supported languages

Prerequisites

  • Basic programming experience in at least one language (C#, Java, JavaScript, Python, TypeScript, or Rust)
  • Understanding of the client-server model and REST/HTTP concepts
  • Familiarity with command-line tools
  • Background in AI/ML concepts and large language models
  • Experience with cloud platforms (Azure concepts appear in Modules 5 and 11)
  • Docker and containerization basics (used in Lab 10)
  • A code editor (VS Code recommended — many examples show VS Code integration)
  • Git for cloning the repository
  • Language-specific runtimes for your chosen language (.NET, Node.js, Python, JDK, Rust)

Community & Support

GitHub Repository

Star the repo, open issues, and contribute examples

Microsoft Foundry Discord

Connect with fellow learners and MCP experts

MCP Documentation

Official MCP documentation and specification

MCP Specification

Full protocol specification (2025-11-25)

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