LEARN AI / HOW IT WORKS

Agents, harnesses, tools, and MCP.

Understand the parts behind a tool-using AI workflow.

IntermediateHow it worksReviewed 2026-11-05

THE LESSON

Let's understand the essentials.

PART 01

An agent is a system that chooses actions toward a goal. A harness is the surrounding software that coordinates the model, tools, memory, permissions, evaluation, and runtime. MCP is a protocol for connecting models and agents to external tools and data.

PART 02

The harness, not the model alone, determines which actions are actually possible and safe. Permission boundaries, approval points, and failure handling matter as much as the prompt.

PART 03

Draw a flow diagram with user goal, model, tool calls, permissions, logs, review, and fallback.

CHECK YOUR UNDERSTANDING

Why doesn't giving an agent a new MCP server automatically make it reliable?

Explain your answer in your own words, then compare it with the main concepts above.

Suggested reference: Read the underlying documentation or source ↗. Educational content is reviewed as of 2026-11-05; model interfaces and availability may change.
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