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Introduction to Model Context Protocol

by Anthropic · Anthropic

2 hoursUpdated 2026-06

Our Verdict

Worth taking

"Introduction to Model Context Protocol" is Anthropic's free, official course on MCP, the open standard it created for connecting AI models to external tools, data, and prompts. It is hands-on and Python-based, walking you through building both MCP servers and clients around the protocol's three core primitives: tools, resources, and prompts. Learning MCP from its originator is a meaningful advantage, since the conventions and best practices here are authoritative rather than second-hand. It is aimed at developers comfortable with Python and assumes you want to write code, not just understand MCP conceptually. A strong, practical pick for engineers building agentic or tool-augmented systems, especially within the Claude ecosystem.

Free, first-party instruction on a standard Anthropic itself created, taught hands-on in Python; for developers who need to build with MCP, learning it from the source is hard to beat.

Best for: Python developers building agentic or tool-augmented AI systems who want to learn how to implement MCP servers and clients and wire up tools, resources, and prompts.

Skip if: Non-developers, people who want only a high-level conceptual overview of MCP, or those not working in Python or within the Claude/MCP ecosystem.

About This Course

Anthropic's free, hands-on course on the Model Context Protocol (MCP), teaching you to build MCP servers and clients in Python around its three core primitives: tools, resources, and prompts.

What You'll Learn

What the Model Context Protocol is and why it exists as an open standard
MCP's three core primitives: tools, resources, and prompts
How to build an MCP server in Python and define tools on it
How to use the server inspector to test and debug an MCP server
How to implement an MCP client and connect it to a server
How to define and access resources and define prompts, and use them from a client

Curriculum

Introduction

Welcome, introducing MCP, and MCP clients.

Hands-on with MCP servers

Project setup, defining tools, and using the server inspector.

Connecting with MCP clients

Implementing a client, defining/accessing resources, and defining prompts and using them in a client.

Assessment and wrap-up

Final assessment and MCP review.

Prerequisites

  • Comfortable writing Python
  • Basic understanding of APIs and how AI assistants use tools
  • A working Python development environment

Instructor

Anthropic

Instructor · Anthropic

Pros & Cons

Pros

  • Free, first-party course on a standard Anthropic itself created, so guidance is authoritative
  • Genuinely hands-on: you build both an MCP server and a client in Python
  • Clear, focused scope around MCP's three primitives (tools, resources, prompts)
  • Directly relevant to building modern agentic and tool-augmented AI applications

Cons

  • Requires Python proficiency; not suitable for non-developers
  • Narrow by design; assumes you already want to work with MCP specifically
  • No public star rating or review count to independently verify quality
  • MCP tooling is young and evolving, so specifics may change over time

Alternatives To Consider

How we reviewed this course

This is an independent editorial assessment by Cursarium, based on Anthropic's published course materials and aggregated public learner feedback (last reviewed 2026-06). We have not independently completed the course. Links to providers are standard references, not paid placements.