MCP and A2A alone won’t scale AI agents

Arpita Soni, a senior member of IEEE, says that MCP and A2A solve two different layers of the agentic stack. “MCP is the vertical connection and standardizes how a single agent accesses external tools, data sources, and APIs, replacing the old pattern of writing a custom integration for every tool an agent needs. A2A is the horizontal connection, and it standardizes how independently built agents discover each other, negotiate capabilities, and hand off tasks, regardless of which framework or vendor built them. MCP gives each agent its own hands and eyes (tools and context or capabilities), while A2A gives separate agents a shared language to talk to one another and delegate work,” Soni says.

MCP and A2A are protocols, but scaling AI agents requires layers of capabilities developed on top of them. Here are four at the top of the list: identity and authorization, connecting AI agents to the business’s context layer, business process re-engineering, and developing agenticops capabilities.

Managing identity and authorizations

MCP and A2A define how agents present credentials but don’t govern them. You’re responsible for defining the agent’s identities, what resources they can access, and which agents they can converse with.