Free course

Tool Use & MCP: Connecting AI to the World

Turn prompting into engineering: define JSON-Schema tools, run a real agent loop, and build a spec-shaped in-memory MCP server in your browser.

CoreAgentic AICertificate
6 modules 34 lessons 10 enrolled ~7h of material
Tool Use & MCP: Connecting AI to the World

By the end

What you'll build

  • Explain why an LLM cannot act on the world or fetch live data on its own, and what a tool call adds.
  • Write a valid tool definition in JSON Schema using type, properties, required, enum, and descriptions.
  • Trace the think -> call -> observe -> repeat agent loop and identify its healthy stop conditions and step caps.
  • Distinguish protocol-level errors (JSON-RPC error objects and codes) from tool-level errors (isError results) and craft each.
  • Read a failing agent trace, locate the failure span, and classify it (e.g. ignored-error 'corrupt success').
  • Describe MCP's host / client / server architecture, its transports, and the M x N problem it solves.
  • Hand-craft the MCP initialize handshake and core JSON-RPC messages (tools/list, tools/call).
  • Build a spec-shaped in-memory MCP server that dispatches initialize, tools/list, and tools/call with correct error codes.
  • Run a real single-tool agent loop and reason about grading final state and required tool calls, not prose.
  • Deploy a real MCP server on your own machine via the official quickstart and verify it via the initialize handshake and tools/list.

The shape of it

How this course works

Short lessons

34 lessons across 6 modules, each small enough to finish in one sitting.

Practice as you go

Every lesson ends with a small space for what you noticed — the doing is the learning.

A certificate at the end

Finish the course and earn a certificate anyone can verify with a link.

Ready when you are.

Make an account and this course opens up — your progress is saved from the very first lesson.