MCP for Beginners

What MCP is, briefly

The Model Context Protocol defines how an AI application (the host, such as a chat app, IDE or agent) connects to servers that expose tools, resources and prompts. Build a server once for your database, API or file system, and any MCP-compatible client can use it. That replaces a tangle of one-off integrations with a single standard.

What the curriculum covers

The course is organised into numbered modules:

• 00 to 01: introduction and core concepts, plus a module on what changed in the 2026-07-28 version of the specification (including a stateless protocol and an extensions framework).
• 02: security threats and best practices, and authorisation patterns.
• 03: getting started, with around fifteen hands-on guides: building a first server and client, connecting an LLM, using servers from VS Code, testing and deployment.
• 04 to 05: practical implementation (SDKs, debugging, pagination) and advanced topics such as multi-modal use, OAuth2, Azure integration and scaling.
• 06 to 09: community contributions, lessons from early adopters, best practices and case studies.
• 10 to 12: a workshop, a set of 13 hands-on labs building a PostgreSQL-backed retail analytics server, and tooling.

Before you start

• Basic programming in one of the sample languages.
• A grasp of the client-server model, REST and HTTP.
• AI or machine learning background is optional.

Most early modules run locally with no cloud account. Some advanced modules and the workshop use Azure services.

Popularity and upkeep

The repository had about 17,000 GitHub stars as of September 2026, was updated that month, and is translated into more than 50 languages, including Urdu, Hindi and Bengali. It is MIT licensed, with a Discord community for questions.

A weekend plan

1. Saturday morning: modules 00 and 01, then read the security module. MCP servers can expose powerful tools, so security is not optional.
2. Saturday afternoon: build the first server in your language and connect it to a client such as VS Code or an AI desktop app.
3. Sunday: wrap a real internal thing you care about, such as a small database, a notes folder or an API you use, as an MCP server with two or three tools, and test it with the inspector.
4. Save the advanced modules and labs for when you need them.

Common questions

Do I need to know about agents first? No, but understanding tool or function calling helps. Microsoft's Generative AI for Beginners covers it.

Is MCP only for Microsoft tools? No. It is an open protocol supported by many AI apps and frameworks; the course just uses Microsoft tooling in places.

Is the content current? It tracks specification changes, including a dedicated module on the 2026-07-28 revision, but check the official specification when something looks different.

Best for: developers who want to expose their tools and data to AI apps in a standard, secure way.