Model Context Protocol (MCP): The Universal AI Connector

Every AI tool has its own way of connecting to external services, creating a fragmented ecosystem of bespoke integrations. The Model Context Protocol (MCP) changes that. It is an open standard that gives AI models a universal way to discover and use tools, access data, and interact with services — without custom code for every integration. Think of it as USB-C for AI. This path explains MCP from the ground up and shows how it builds on function calling to create interoperable AI systems.

What You'll Learn

  • 1The integration problem MCP solves and why the AI ecosystem needed a standard protocol
  • 2How MCP works: the client-server architecture behind universal AI connectivity
  • 3MCP servers and clients: who provides capabilities and who consumes them
  • 4Resources vs tools in MCP — two distinct patterns for two types of AI interaction
  • 5Function calling foundations: the mechanism MCP standardizes and extends
  • 6Building with MCP: how to create and consume MCP servers in practice

Curated Lessons (7)

Free, interactive lessons you can complete on your phone in 5-10 minutes each.

The Integration Problem

MCP — The Universal Connector

~7 min

What Is MCP?

MCP — The Universal Connector

~8 min

MCP Servers and Clients

MCP — The Universal Connector

~7 min

Resources vs Tools in MCP

MCP — The Universal Connector

~7 min

Building with MCP

MCP — The Universal Connector

~8 min

What Is Function Calling?

Function Calling & Tool Use

~8 min

Tool Definitions

Function Calling & Tool Use

~7 min

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