Modern AI Engineering

Lesson 11.8 · 27 min · video lesson

Model Context Protocol: A Standard Interface for Agent Tools

If every AI app needs its own custom connector to every tool, who writes the thousands of integrations, and is there a better way?

In short: MCP (Model Context Protocol) is an open standard, introduced by Anthropic in November 2024, for connecting AI applications to tools and data. An AI app (the host) runs MCP clients that talk to MCP servers using JSON-RPC 2.0 messages; servers advertise tools, resources and prompts that the app can discover and use at runtime. Build a server once and any MCP-compatible app can use it, turning an N × M integration problem into N + M, but servers are code you run with real access, so trust and permissions matter.

What you will learn

  • The problem before MCP
  • What is MCP?
  • MCP = Model + Context + Protocol
  • The USB-C analogy
  • How it is different from a normal API
  • The three parts of MCP
  • How it all works step by step
  • How the connection happens
  • A real example
  • Importance of MCP
  • Things we must be careful about
  • Summary

In this lesson

  1. The problem before MCP
  2. What is MCP?
  3. MCP = Model + Context + Protocol
  4. The USB-C analogy
  5. How it is different from a normal API
  6. The three parts of MCP
  7. How it all works step by step
  8. How the connection happens
  9. A real example
  10. Importance of MCP
  11. Things we must be careful about
  12. Worked example, step by step
  13. Practice: try it yourself

Key terms in this lesson

MCP (Model Context Protocol)
An open standard for connecting AI applications to external tools, data and prompts.
Host
The AI application a user interacts with, which manages MCP clients, the model, and permissions.
MCP client
The connector inside a host that maintains a one-to-one session with a single MCP server.
MCP server
A program that exposes tools, resources and prompts to MCP clients, locally or remotely.
JSON-RPC 2.0
A lightweight standard for requests, responses and notifications encoded as JSON, used by all MCP messages.
Transport
How MCP messages travel: stdio for local subprocesses or Streamable HTTP for remote servers.
Resource
Read-only data a server exposes, identified by a URI, that the host can add to the model's context.

This lesson is part of the Generative AI Engineering and Complete AI Engineer tracks. See plans and pricing to open the full lesson, its video, labs and quiz, or try the free lesson first (free account needed).

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