• Speaker: Justin Castilla
• Room: CC 234
• Time: Sat 2:00 pm – 2:30 pm

• Format: Lecture (30 Min + Q&A)
• Difficulty: Introductory
• Track: AI / ML
• Presenter Location: In-person
• Experience: umpteenth time speaking

Modern AI applications are evolving beyond single chatbots into networks of specialized agents working together. Agent2Agent (A2A) is a protocol that enables AI agents to communicate and collaborate — for example, in a digital newsroom where a Reporter agent writes stories, a Researcher gathers facts, an Editor reviews quality, and an Archive agent retrieves historical context. A2A coordinates *who talks to whom*.

But each agent also needs access to tools and data. This is where Model Context Protocol (MCP) comes in, providing standardized access to databases, APIs, and other resources. MCP handles *what tools each agent can use*.

This talk demonstrates how A2A and MCP complement each other through a practical newsroom example. Attendees will learn:

• When to use A2A for multi‑agent coordination
• When to use MCP for tool and data integration
• How to implement both protocols in real applications
• Why combining them leads to more maintainable, scalable systems

Developers will leave with a clear understanding of how to build distributed agent systems that leverage specialization, autonomy, and standardized tool access to accomplish complex workflows that single agents struggle to handle efficiently.

Target Audience:

• AI/ML developers
• ML DevOps practitioners