AI Agent Protocols: Not All Agents Talk the Same

As AI systems multiply and evolve, a new question is emerging in every enterprise boardroom:

“How do these AI agents actually communicate with each other?”

Whether you’re designing automation systems, building AI-powered tools, or trying to make your enterprise platforms smarter — understanding agent communication protocols is critical. At DataCouch, we help organizations navigate this complexity through enablement, consulting, and hands-on implementation — so teams can build the right systems with the right communication models from day one.

Let’s unpack the four most prominent agent communication protocols — developed by some of the world’s leading tech players — and understand how they differ.

🤖 Meet the Protocols: 4 Unique Styles of AI Communication

1. MCP — Model Context Protocol (by Anthropic)

Style: Straightforward & tool-savvy

• Uses a client-server model
• Agents must be manually registered
• Doesn’t remember previous sessions (stateless)
• Best at: Tool calling
• Trade-off: No memory, no fancy negotiations