MCP vs A2A
MCP and A2A standardize different boundaries in an agent system. The Google launch announcement explicitly calls them complementary. Google A2A announcement
Comparison
| Dimension | MCP | A2A |
|---|---|---|
| Primary boundary | AI application or host ↔ data/tool server | Client agent ↔ remote agent |
| Primary purpose | Expose context and callable capabilities | Discover agents and coordinate tasks |
| Counterpart model | Server with defined capabilities | Autonomous peer or specialist |
| Interaction shape | Capability discovery and invocation | Messages, task lifecycle, status, artifacts |
| State expectation | Often bounded by individual capability calls | May be long-running, stateful, and clarifying |
| Discovery concept | Server or capability definitions and registries | Agent Cards and agent discovery |
| Orchestration effect | Expands the host’s available tools | Coordinates work across agent boundaries |
| Core risk | Untrusted capability, excess permissions, unsafe output | Delegated authority, spoofed peers, state and task confusion |
The MCP launch source describes shared client–server connections to data and tools. The A2A source describes client and remote agents collaborating through tasks, messages, and artifacts. Anthropic MCP announcement · Google A2A announcement
The later Google interoperability whitepaper supplies additional protocol-layer detail but remains vendor-authored rather than independent conformance evidence. Tools and interoperability source record
When MCP is the better fit
Prefer an MCP-like boundary when the remote capability is well described as data access or a bounded operation and the host should retain the main control loop. Examples include querying a repository, reading a database, or invoking a constrained action.
When A2A is the better fit
Prefer an A2A-like boundary when the remote participant has meaningful autonomy, may ask for clarification, maintains task state, streams progress, or produces artifacts over a long-running collaboration.
Where the boundary blurs
A sophisticated tool can be asynchronous and stateful, while a narrowly scoped agent may behave like a tool. The labels do not resolve architecture automatically.
Analysis: Select the simpler contract that preserves required semantics. Do not introduce peer-agent delegation when a bounded tool call is sufficient; do not flatten an independently governed, stateful collaborator into a brittle request–response call.
Shared requirements
Both boundaries still need:
- version and capability negotiation;
- authentication and authorization;
- input and output validation;
- error, timeout, and cancellation semantics;
- observability and audit records;
- conformance and interoperability testing.
See Agent interoperability, Agent tools, and Agent orchestration.
Evidence limits
Both launch announcements are historical and promotional. They establish original intent, not current protocol behavior or comparative performance. The Google whitepaper adds architectural detail but remains vendor-authored. Current implementations must use versioned specifications.