The Agent2Agent (A2A) Protocol is an open standard for communication between independent AI agents — systems that may be built on different frameworks, run by different vendors, and keep their tools and memory private. Instead of forcing every agent to become a brittle API wrapper or a single mega-orchestrator, A2A defines a common way for agents to discover each other, negotiate capabilities, delegate work as tasks, and exchange messages and artifacts.

Why it matters: multi-agent products are no longer demos. Enterprises want a research agent to hand work to a CRM agent, or a vendor agent to collaborate with an internal policy agent, without sharing prompts and tool secrets. The official overview at a2a-protocol.org’s “What is A2A?” and Google’s announcement of A2A as an interoperability layer frame the same bet: agents need a lingua franca the way services needed HTTP and OpenAPI.

What A2A Actually Standardizes

A2A, originally developed by Google and donated to the Linux Foundation, specifies how opaque agents interact without exposing internals. Core ideas include the Agent Card (a machine-readable capability and endpoint description, often published at a well-known URL), Tasks as stateful units of work with lifecycle states, and Messages made of typed Parts that can carry text, files, or structured data, plus Artifacts as durable outputs. Bindings cover JSON-RPC over HTTP (with streaming via Server-Sent Events), gRPC, and HTTP+JSON patterns, with a normative protobuf definition as the source of truth for the data model.

Discovery is intentional: clients fetch an Agent Card, learn supported interfaces and protocol versions, then send task-oriented requests rather than inventing a one-off chat schema per partner. That is what makes cross-vendor collaboration feasible at scale.

A2A vs MCP vs “Just Call an API”

Teams often ask whether A2A replaces the Model Context Protocol (MCP). It does not. A2A’s own MCP comparison draws a clean line: MCP is primarily about connecting an agent to tools, data sources, and context providers; A2A is about agent-to-agent collaboration when each side may keep its tools and reasoning private. Wrapping another agent as a single tool can work for simple call-and-response, but it breaks down for long-running delegated work, negotiated capabilities, and opaque peers you do not control.

Plain REST APIs still matter for deterministic services. A2A sits one layer up: when the peer is itself an agent — with goals, multi-step state, and asynchronous results — you need task semantics, streaming updates, and capability cards more than a static OpenAPI file. In real stacks, MCP-style tool bridges and A2A compose: an agent uses tools locally, then collaborates with other agents over A2A. For the architecture side, see how multi-agent architectures split work across specialized agents, and why context engineering decides what each agent actually knows when it receives a task.

What Production Teams Must Get Right

Interoperability without governance is chaos. Publish accurate Agent Cards, pin protocol versions, authenticate with the modern OAuth or mutual TLS patterns the spec supports, and treat tasks as auditable work items — not fire-and-forget chat. Pair A2A with AI guardrails, eval suites, and clear ownership so a delegated agent cannot silently widen permissions. Remote peers are also a new surface for prompt injection, so treat incoming messages and artifacts as untrusted input. Measure end-to-end task success, latency, and failure codes the way you already measure tool calls.

Common Mistakes Teams Make

Teams paste a demo Agent Card and never update capabilities after shipping new tools. Others force every peer through a central mega-agent that reimplements agent messaging ad hoc. Some conflate MCP tool servers with A2A peers and wonder why long-running collaboration feels awkward. And many skip security: an Agent Card on the public internet without authentication is an invitation. Start with one trusted partner agent, version the card, log every task, and expand only after evals and access control hold.

If you are building agents that must collaborate across teams and vendors, structured practice helps. Explore Coderhouse’s courses below.

• AI Engineering Course — strengthen agent design, evaluation, and production architectures.

• Data Analytics Course — ground agent decisions in trustworthy data and measurement habits.

FAQ

Is A2A only for Google agents?

No. A2A is an open, Linux Foundation–hosted standard with multi-vendor steering and SDKs across several languages. Any conforming agent can publish a card and speak the protocol.

Do I still need MCP if I adopt A2A?

Usually yes for tool access. MCP (or an equivalent) connects an agent to tools and data; A2A connects agents to each other. Most serious stacks will use both.

What is the smallest useful A2A pilot?

Expose one internal agent with a correct Agent Card, let a second agent create tasks against it for a narrow workflow, and measure task completion, authentication failures, and human escalation rate before adding more peers.