As enterprises move from isolated AI agents to ecosystems of specialized agents, interoperability becomes essential. Agents need to securely share context, access tools, and delegate work across frameworks, systems, and organizational boundaries without creating a web of point-to-point integrations. This is where MCP and A2A come in — MCP standardizes agent-to-tool and data access, while A2A enables agent-to-agent collaboration. This article explores how they fit together, where execution hooks provide deterministic control, and how architects can decide when to use each.
Two protocols, two different jobs, and the distinction matters for architecture decisions, not just vocabulary:
Both now sit under Linux Foundation governance alongside IBM’s ACP, with a working group spanning Anthropic, OpenAI, Google, Microsoft, AWS, Block, Cloudflare, and Bloomberg — which matters architecturally because you’re adopting a jointly maintained standard, not betting on one vendor’s spec surviving.
MCP and A2A are stateless. Neither tracks what an agent did, what data it touched, or how an output was used — audit trail, policy enforcement, and lineage are not native to either spec. That gap is measurable: independent 2026 scans found upwards of 12,000 MCP servers exposed to the public internet, roughly 40% with no authentication, and more than half still running static credentials instead of OAuth. A critical npm package vulnerability in the ecosystem exposed 400,000+ installations to shell injection earlier this year. None of this is a protocol flaw — MCP and A2A were designed as communication standards, not governance layers. It’s what happens when adoption outpaces the enforcement layer underneath it.
The enforcement layer is the Agent Control Plane from part two of this series: tool allowlisting, policy-as-code (OPA), circuit breakers, identity tied to an owning entity. Treat every MCP server and A2A endpoint as a security boundary, not a convenience layer.
A tool is probabilistic — the LLM decides whether and when to call it. A hook is deterministic — it fires unconditionally at a defined point in the execution loop, every time, regardless of what the agent decided. Different category of control, not a difference of degree. A tool gives an agent hands; a hook is what the agent’s hands can’t argue past.
Two hook types carry the actual enforcement weight:
Two minimal, concrete examples:
Neither involves model judgment — both are structural checks that run on every call. Most current implementations let you scope a hook with a matcher pattern rather than firing on everything: a matcher targeting the mcp__<server>__<action> naming convention hooks MCP tool calls specifically, and the same mechanism wraps an outgoing A2A delegation before it leaves the orchestrator. This is where the control plane stops being a diagram and becomes code — the pre-execution hook is typically the integration point that calls out to an OPA policy decision, checks the allowlist, or trips a circuit breaker, before the MCP call or A2A handoff is allowed to proceed.
Protocol and enforcement choices should follow architecture classification, not a vendor’s marketing description. A practical breakdown:
Start by documenting every agent, tool, data source, and human approval point, with a named technical owner, business owner, and security boundary for each. That classification — not the protocol’s popularity — determines which of the above applies. In practice: adopt MCP without hesitation, since wrapping internal capabilities as MCP servers is the highest-return integration work available right now. Adopt A2A only once there are genuinely multiple agents that need to interoperate across teams, frameworks, or organizations — later than most projects assume they’re at.
Hooks are dense enough to eventually warrant their own dedicated two-part treatment — this piece covers what’s needed to use them well today.
Companion piece: why interoperability and execution hooks matter for the business side — where to use them and what they mean for cost, risk, and vendor selection. Next in the core series: how sovereign AI requirements reshape program delivery.
Multi-Agent Interoperability: A Technical Deep Dive into MCP, A2A, and Execution Hooks was originally published in Towards AI on Medium, where people are continuing the conversation by highlighting and responding to this story.