Learn MCP — The Complete Free Model Context Protocol Course

Before USB-C, every device had its own cable and every laptop its own drawer of adapters. AI tooling was in exactly that state until recently: every AI application wrote its own connector for every system it needed. MCP — the Model Context Protocol — is the USB-C moment for AI tools, and it's the newest term appearing in AI job descriptions and interviews. This short, free course teaches it properly: the architecture, the three primitives, transports, building a server, security, and how to talk about it in an interview.

What is MCP?

MCP is an open protocol for connecting AI applications to tools and data. A system's owner publishes one server describing what it offers; any MCP-capable client can connect and use it. No bespoke integration per pairing.

A server can expose three kinds of thing — and the distinction between them is the most-asked MCP interview question: tools (actions the model can call), resources (read-only data the application can load), and prompts (templates the user can pick). Lesson 3 makes that split precise.

The problem it solves

Say your company has four AI applications and six internal systems. Without a standard, that's up to 24 integrations— each separately built, secured and maintained, each reinventing auth and error handling, and each needing a fix when one API changes.

With MCP: six servers. Any application connects to whichever it needs, a fifth application costs zero integration work, and an API change is fixed once. MCP is an integration-economics problem, not an intelligence problem — it doesn't make the model smarter, it makes capability plug in.

Your first MCP server — right now

The SDKs are deliberately boring: annotate an ordinary function and the schema is generated for you.

from mcp.server.fastmcp import FastMCP

mcp = FastMCP("orders")

@mcp.tool()
def get_order(order_id: str) -> dict:
    """Get the status and items of a customer order by its numeric id.
    Use for questions about a specific order. Does NOT search policies."""
    if not order_id.isdigit():
        return {"error": f"order_id must be numeric; got {order_id!r}"}
    return db.find_order(order_id) or {"error": "no such order"}

if __name__ == "__main__":
    mcp.run()          # stdio transport by default

tools: get_order — Get the status and items of a customer order…

Notice what the docstring became: the description the model reads to decide whether to call this tool. In MCP, your docstrings are prompts — a theme that runs through the whole course.

Why learn MCP (the honest version)

One: it's the newest keyword in AI interviews and the least crowded — dedicated MCP question banks already exist, and far fewer candidates can answer them well than can discuss RAG. Two: it's becoming the plumbing of the agent ecosystem, so understanding it makes the rest of your AI stack knowledge fit together. Three: it's small — a genuinely learnable topic in a few sittings, unlike RAG or agents, which makes it excellent return on study time before an interview.

How this course works

Nine short lessons, each with intuition, diagrams, runnable Python where useful, and a Practice Zone of MCQs and hands-on tasks with the companies where each pattern has been asked.

Prerequisite: you should understand tool/function calling — that the model emits a request and your code executes it. If that's new, read the GenAI course lesson on APIs and function calling or the agents course lesson on tool calling first.

Course roadmap — 9 lessons

Company-wise MCP PYQs

After the lessons, a set of company-wise MCP interview questions — reported patterns from Microsoft, Google, Amazon, Infosys, TCS and Accenture — in attempt-then-reveal format.

How to study this course

It's short enough to read in two sittings. If you have only thirty minutes before an interview, read lessons 1, 3 and 7 — the problem, the primitives, and the security story. And build the fifteen-line server from lesson 5; being able to say "I wrote one" puts you ahead of nearly everyone else answering MCP questions from memory.

FAQ

Ready? Start here — Lesson 1: What Is MCP? →