If you've spent any time building with AI agents in the last year, you've run into both acronyms: MCP and A2A. They get lumped together constantly, compared in tables, pitted against each other in "which one should I use" threads. But that framing is off. MCP vs A2A isn't really a versus fight — they solve different problems and mostly show up in different layers of an agent system.
This post breaks down what each protocol is actually for, where they overlap (barely), and where the real gaps are once you start building multi-agent systems that need to talk to each other over the open internet.
MCP: giving one agent access to tools and data
Model Context Protocol (MCP), from Anthropic, solves a narrow, well-defined problem: how does a single LLM-driven agent call out to external tools, files, databases, or APIs in a standardized way?
Before MCP, every agent framework invented its own tool-calling format. A tool that worked in one framework needed a rewrite to work in another. MCP standardizes the interface: an MCP server exposes a set of tools (and resources, and prompts) with typed schemas; an MCP client — usually embedded in your agent runtime — discovers those tools and calls them.
Think of MCP as the interface between an agent's reasoning loop and the world of tools it can act on. A single agent process talks to N MCP servers. It's local-ish in spirit even when the server is remote — the relationship is "one brain, many hands," not "agent talking to another independent agent with its own goals."
Practical shape of an MCP interaction:
- Agent asks: "what tools do you have?"
- MCP server replies with a schema: tool names, parameters, descriptions.
- Agent calls a tool with arguments, gets structured JSON back.
- Agent folds the result into its next reasoning step.
That's it. No concept of the other side having its own autonomy, its own conversation history with a user, or its own long-running task state. It's a request/response tool bus.
A2A: agent-to-agent, as peers
Agent2Agent (A2A), originally from Google and now under Linux Foundation stewardship, is aimed at a different problem: how do two independent agents — possibly built by different teams, on different frameworks, with different capabilities — collaborate on a task as peers?
The key word is peers. In A2A, both sides are agents with their own reasoning, their own state, and potentially their own users. A2A defines things MCP doesn't need to care about:
- Agent Cards — a discoverable manifest describing what an agent can do, similar in spirit to an MCP tool list but scoped to a whole agent's capabilities rather than a tool server's.
- Task lifecycle — A2A tasks aren't a single request/response; they have states (submitted, working, input-required, completed) because agent-to-agent collaboration is often long-running and needs back-and-forth.
- Multi-turn negotiation — an agent can ask a peer agent for clarification mid-task, not just fire-and-forget a call.
So while MCP answers "how does my agent use a tool," A2A answers "how does my agent delegate part of a task to another agent that isn't under my control, and follow that task to completion."
Why they're not actually competing
Once you frame it that way, the overlap shrinks: MCP is the tool-calling layer inside an agent; A2A is the collaboration protocol between agents. A sophisticated multi-agent system plausibly uses both — an orchestrator agent might use A2A to delegate a subtask to a specialist agent, and that specialist agent might use MCP internally to call its own tools while working on the task.
The confusion mostly comes from the fact that both use similar plumbing (JSON-RPC-ish request/response, capability discovery, structured schemas) and both got hyped as "the" agent interoperability standard at roughly the same time. But "how does an agent use a tool" and "how do two independent agents collaborate" are genuinely different design problems, and neither protocol tries to fully solve the other's problem.
What neither protocol solves: the network layer
Here's the part that gets glossed over in most MCP-vs-A2A writeups: both protocols describe a message format and interaction pattern — they don't solve how the underlying connection actually gets established and stays alive between two agents that might be behind NAT, on different clouds, or restarting on different schedules.
If your MCP server sits behind a firewall, or your A2A peer's IP changes because it redeployed, you're back to solving networking problems yourself: exposing ports, managing webhooks, rotating tunnel URLs, or standing up a message broker just to get bytes from A to B reliably.
This is the gap Pilot Protocol was built for. It's an open-source overlay network that gives every agent a permanent virtual address — one that survives IP changes, restarts, and moving across clouds — plus encrypted UDP tunnels (X25519 key exchange, AES-GCM) and NAT traversal via STUN, hole-punching, and relay fallback. Trust is explicit: a mutual per-peer handshake, decoupled from network membership, so being reachable doesn't mean being trusted.
Concretely, that means an A2A-style "agent asks another agent to do something" flow doesn't need a public endpoint or a webhook relay in front of it — the two agents just need to be Pilot peers:
pilotctl handshake <peer-hostname> "collaborating on task X"
pilotctl send-message <peer-hostname> --data '<task payload>'
And for the MCP side, Pilot ships an MCP server (pilot-mcp) that exposes the overlay network — peer discovery, messaging, the specialist-agent directory — as MCP tools an agent can call directly, so an MCP-based agent can reach into the peer-to-peer layer without leaving its normal tool-calling flow.
There's also an app store layer worth knowing about if you're building either kind of agent: pilotctl appstore catalogue lists installable, agent-native capabilities that run locally as typed JSON-in/JSON-out services — install one with pilotctl appstore install <id>, then call it directly. It's a discover → install → call loop that complements both MCP (local tool access) and A2A (remote agent collaboration) without replacing either.
A simple mental model
| Question | Protocol |
|---|---|
| "How does my agent call this tool/API?" | MCP |
| "How does my agent hand off a subtask to another independent agent?" | A2A |
| "How do these two agents actually find each other and stay connected across NATs, restarts, and IP changes?" | Neither — that's a networking problem, which is what Pilot Protocol addresses |
If you're building a single agent that needs structured access to tools and data, reach for MCP. If you're building a system where independent agents need to negotiate and delegate work to each other, reach for A2A. And if either of those agents needs to actually stay reachable on the open internet without you hand-rolling tunnel and NAT-traversal code, that's the layer underneath both protocols — not a replacement for either.
FAQ
Is A2A a replacement for MCP?
No. A2A operates between independent agents; MCP operates between an agent and its tools. Many production systems use both at different layers of the same stack.
Can I use MCP and A2A together?
Yes. A common pattern is an orchestrator agent delegating to peer agents over A2A, where each peer agent uses MCP internally to access its own tools.
Does Pilot Protocol replace MCP or A2A?
No — it operates one layer down, at the network/transport level. It gives agents a permanent address, encrypted tunnels, and NAT traversal, and it ships an MCP server so MCP-based agents can use the overlay network as a tool. It doesn't redefine tool-calling or agent task semantics.
Which one should I learn first?
If you're building your first agent, start with MCP — it's the simpler, more contained problem. A2A becomes relevant once you're coordinating multiple independent agents.
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