As autonomous agents become more capable, coordinating their interactions with tools and with each other has become a critical challenge. In this session, we’ll introduce the emerging landscape of Agentic AI protocols — with a focus on MCP (Model Context Protocol), A2A (Agent-to-Agent Protocol), and ACP (Agent Communication Protocol). These AI protocols are laying the foundation for interoperability, scalability, and real-world adoption of agentic AI.
We’ll begin with an overview of the multi-agent coordination challenge — why multiple agents require shared standards for communication, negotiation, and orchestration. Then we’ll explore how MCP, developed by Anthropic, provides a “USB-C for AI” that enables seamless integration with thousands of external tools. Building on this, we’ll look at A2A for direct agent-to-agent coordination and ACP for creating a common messaging language between heterogeneous agents.
You’ll also see a live demo of Zapier’s MCP integration, showing how an AI agent can trigger multi-step workflows across 7,000+ apps — extended with a multi-agent scenario to illustrate how protocols complement each other in practice. Finally, we’ll compare MCP, A2A, and ACP, and discuss strategies for designing scalable, standards-based agent systems.
Through live demos and audience Q&A, participants will gain hands-on insights into MCP-powered automation and explore how emerging protocols like A2A and ACP extend agent capabilities for real-world, multi-agent systems.
Senior Data Scientist at Data Science Dojo | 5x Azure Solutions Architect