As AI in Power Platform and Copilot Studio shifts from isolated agents and LLM calls to networks of automation, two models are emerging for “how stuff talks to other stuff”: Model Context Protocol (MCP) providing server-backed tool exposure, and agent-to-agent (A2A) orchestration. They overlap, but they’re not the same — and that includes the crucial security and governance controls we can apply to each.

This session unpacks that difference and how they can be governed and secured today.

We’ll look at MCP as the “USB-C for AI”: a predictable, admin-governable way to expose capabilities, data, and actions to AI models and agents. Then, we’ll contrast it with Agent-to-Agent patterns, where one agent calls or delegates to another — a flexible model, but harder to control and predict with different risks: who can call whom, with what data, and under which contexts.

What you’ll learn:

1. Where MCP is stronger than A2A, and how to discover and manage MCP servers across your tenant to define ownership and access.

2. Where A2A could be preferable to MCP, including considerations for multi-cloud scenarios.

3. A practical roadmap — which security and governance actions to take now, and what to watch for going forward.

This session is aimed at Power Platform admins, security and governance leads, and platform owners who need to let AI connect to real systems without losing control. You’ll leave with a side-by-side mental model of MCP vs. Agent-to-Agent, and a list of guardrails you can actually implement.