On standards and AI agents: a walkthrough of MCP, A2A, ADK and more

AI agent foundations are built over a handful of common protocols that you need to master, to make the best out of your LLM and agent framework. That’s why it’s important to understand them. But some are catching up, others are not.

In this deep dive, we will explore the ecosystem showing you these standards and focusing on the important ones. Knowing some of the frameworks is useful too to get started faster. Welcome MCP, A2A, ACP protocols, and ADK, Arc, Quarkus, LangChain4j frameworks!

After giving you an overview of the main standards and protocols, their merit and their popularity, we will start by building an agent using Agent Development Kit (ADK) and walk through making a tool call. From there, zooming on MCP, we’ll see how to standardize that tool via a local MCP server and then deploy it as a remote MCP server to share it with others.

Next, we’ll dive into the A2A protocol and enable our agent to participate in multi-agent conversations. And to do that, we will use another framework, Quarkus and LangChain4j, showing how different stacks interact seamlessly through A2A.

You’ll learn not just what these protocols do and how they work, but why they matter, with detailed walkthroughs and live demos throughout.

If you’re struggling to understand all the protocol details around AI agents, this session is for you!