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AI agents · topic 14 of 16

Agent Protocol Landscape

How MCP, A2A, AG-UI, and adjacent standards relate in one picture from the course deck (PDF 253–255).

Agent Protocol Landscape

● TEXT_MESSAGE_CONTENT for token streaming.

● TOOL_CALL_START to show tool execution.

● STATE_DELTA to update shared state (code, data, etc.)

● AGENT_HANDOFF to smoothly pass control between agents

And it comes with SDKs in TypeScript and Python to make this plug-and-play for any stack, like shown below:

Illustration from the AI Agents chapter of the course deck.
Illustration from the AI Agents chapter of the course deck.

In the above image, the response from the Agent is not specific to any toolkit. It is a standardized AG-UI response. This means you need to write your backend logic once and hook it into AG-UI, and everything just works:

● LangGraph, CrewAI, Mastra—all can emit AG-UI events.

● UIs can be built using CopilotKit components or your own React stack.

● You can swap GPT-4 for Llama-3 locally and not change anything in the frontend. This is the layer that will make your Agent apps feel like real software, not just glorified chatbots. Agent Protocol Landscape Something remarkable is happening in the AI industry.

Earlier the agent ecosystem was fragmented into dozens of incompatible frameworks. But finally, the industry is converging around three protocols that work together. These are:

Illustration from the AI Agents chapter of the course deck.
Illustration from the AI Agents chapter of the course deck.

AG-UI (Agent-User Interaction):

● The bi-directional connection between agentic backends and frontends.

● This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. MCP (Model Context Protocol):

● The standard for how agents connect to tools, data, and workflows.

● Started by Anthropic, now adopted everywhere.

A2A (Agent-to-Agent):

● The protocol for multi-agent coordination.

● How agents delegate tasks and share intent across systems.

These aren’t competing standards. They’re layers of the same stack. AG-UI can handshake with both MCP and A2A, meaning tool outputs and multi-agent collaboration can flow seamlessly to your user interface.

Illustration from the AI Agents chapter of the course deck.
Illustration from the AI Agents chapter of the course deck.

Your frontend stays connected to the entire agent ecosystem through one unified protocol layer. CopilotKit sits above all three as the Agentic Application Framework. It acts as the practical layer that lets you actually build with these protocols without dealing with the complexity. So you get all three protocols, generative UI support and production-ready infrastructure in one framework. The best part: All of this is 100% open-source!

Key takeaways

  • Interoperability wins when protocols cover tools, peers, and human UI together.
  • Expect this landscape to evolve—design for adapters, not hard dependencies.