As AI agents move from demos to production, the need for standardized communication becomes critical. This analysis examines three protocols that are emerging as foundational: MCP (Model Context Protocol) for connecting agents to tools and data, A2A (Agent-to-Agent) for enabling direct agent collaboration, and AG-UI for standardizing how users interact with agents. Each protocol addresses a different layer of the agent stack, and understanding their boundaries is key to building robust systems. The post offers a clear comparison of their purposes, typical use cases, and how they can coexist in a single architecture. For developers evaluating agent frameworks, this landscape is essential knowledge. The protocols are still evolving, but early adoption can provide a competitive edge. This overview serves as a starting point for deeper technical evaluation.
A practical overview of three core protocols defining AI agent interoperability, helping developers understand their roles and trade-offs.