A2A: Agent2Agent Protocol
You may have heard of A2A—the Agent-to-Agent Protocol—but what exactly does it do, and how does it compare to MCP?
The Agent2Agent (A2A) Protocol is an open standard designed to solve a fundamental challenge in the rapidly evolving landscape of artificial intelligence: how do AI agents, built by different teams, using different technologies, and owned by different organizations, communicate and collaborate effectively?
A2A and MCP are highly complementary and address different layers of an agentic system's interaction needs. If MCP is the “USB-C port for LLMs” that connects models to tools and data, then A2A is the operating system for agent collaboration. Where MCP focuses on aligning LLM behavior by providing agents with contextual access to data and tools, A2A tackles a broader, equally crucial challenge: enabling specialized AI agents to work together, across boundaries, technologies, and organizations.
— A2A Overview
Think of A2A as the glue layer that allows disparate agents—perhaps powered by MCP—to discover each other, delegate responsibilities, and co-complete complex tasks. Instead of standardizing the way a single agent uses tools to put the right stuff into its model (LLM) context, A2A lets multiple agents work together.
So, is A2A a natural extension of MCP? Join us live to find out!
Let’s consider an example.
Your travel planner AI assistant needs to:
Book flights (via a travel agent)
Reserve hotels (via a hospitality agent)
Recommend experiences (via a local activity agent)
Monitor exchange rates (via a finance agent)
Without A2A, each integration is brittle and bespoke. With A2A, any compliant agent can find and coordinate with others seamlessly, thanks to open standards for discovery, messaging, and workflows.
A2A aims to:
Break Down Silos: Connect agents across different ecosystems.
Enable Complex Collaboration: Allow specialized agents to work together on tasks that a single agent cannot handle alone.
Promote Open Standards: Foster a community-driven approach to agent communication, encouraging innovation and broad adoption.
Preserve Opacity: Allow agents to collaborate without needing to share internal memory, proprietary logic, or specific tool implementations, enhancing security and protecting intellectual property.
🧠 Join us to explore A2A inside and out—how it builds on familiar web standards, solves agentic interoperability, and compares to MCP in architecture, ambition, and practical deployment.
📚 You’ll learn:
What A2A is, from transport protocol to task coordination
How it compares to MCP and when to use one (or both)
How to build agents that can talk to each other with no prior integration
The principles behind A2A’s async-first, modality-agnostic design
🤖 Who should attend:
AI Engineers building multi-agent systems or AI apps that rely on collaboration
Platform architects working on cross-agent orchestration
Anyone curious about the future of interoperable agent ecosystems
Speakers:
Dr. Greg” Loughnane is the Co-Founder & CEO of AI Makerspace, where he is an instructor for their AI Engineering Bootcamp. Since 2021, he has built and led industry-leading Machine Learning education programs. Previously, he worked as an AI product manager, a university professor teaching AI, an AI consultant and startup advisor, and an ML researcher. He loves trail running and is based in Dayton, Ohio.
Chris “The Wiz” Alexiuk is the Co-Founder & CTO at AI Makerspace, where he is an instructor for their AI Engineering Bootcamp. During the day, he is also a Developer Advocate at NVIDIA. Previously, he was a Founding Machine Learning Engineer, Data Scientist, and ML curriculum developer and instructor. He’s a YouTube content creator YouTube who’s motto is “Build, build, build!” He loves Dungeons & Dragons and is based in Toronto, Canada.
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