A2A Protocol Explained: How AI Agents Collaborate on Commerce

When a user asks an AI to "find me the best running shoes under $150 with good reviews and fast shipping," no single agent has all the answers. A product search agent finds options, a review agent scores them, a shipping agent checks delivery times, and a payment agent handles checkout.

Google's Agent-to-Agent (A2A) protocol is the glue that makes this multi-agent collaboration possible.

What is the A2A Protocol?

A2A is an open standard from Google that defines three core capabilities:

Agent Discovery — Agents publish "Agent Cards" describing what they can do. Other agents discover them via a standardized registry.

Capability Exchange — Before collaborating, agents negotiate capabilities. A shopping agent might need a payment agent that supports Stripe, and A2A finds the match.

Task Delegation — Complex tasks are broken into subtasks and delegated to specialist agents, with A2A managing the handoffs.

How A2A Powers Commerce

Here is a typical A2A-powered shopping flow:

Step 1: User Request

User asks: "Find me wireless headphones with noise canceling, under $300, with the best reviews."

Step 2: Agent Discovery

The primary agent uses A2A to discover specialist agents — a product search agent, a review aggregation agent, and a pricing comparison agent.

Step 3: Task Delegation

• Search agent queries product catalogs via MCP
• Review agent aggregates scores from multiple platforms
• Pricing agent checks for deals and coupons

Step 4: Result Synthesis

Agents report back. The primary agent synthesizes results and presents top 3 options.

Step 5: Transaction

User picks one. The primary agent delegates checkout to a commerce agent using ACP or UCP.

A2A vs ACP vs MCP

These three protocols operate at different layers:

Protocol	Layer	Purpose
A2A	Orchestration	Agent-to-agent coordination
ACP	Transaction	Commerce checkout and payments
MCP	Data	Product catalogs and tools

A2A sits above ACP and MCP. It does not replace them — it orchestrates them.

Deep dive: ACP vs MCP comparison

Agent Cards: How Discovery Works

Every A2A-compatible agent publishes an Agent Card — a machine-readable document describing:

• Name and description — what the agent does
• Capabilities — specific tasks it can handle
• Input/output schemas — data formats it accepts and returns
• Authentication — how to securely connect
• SLA — expected response times and reliability

When an agent needs help, it queries the A2A registry for agents with matching capabilities. This is similar to how microservices use service discovery, but for AI agents.

Why A2A Matters for Brands

If your products are discoverable by AI agents (via MCP or Shopify's MCP endpoint), A2A ensures that multiple agents can find and recommend them as part of coordinated shopping tasks.

Brands that optimize for A2A-compatible agent workflows will appear in more complex, high-intent shopping scenarios — not just simple product searches.

The Future of Multi-Agent Commerce

A2A is still early, but the trajectory is clear. Shopping will increasingly involve teams of specialized AI agents collaborating on behalf of users. The brands that are visible, structured, and transact-ready across this agent ecosystem will capture the most agentic commerce revenue.

Asva AI monitors your brand's visibility across agent-powered shopping workflows and ensures your products are optimized for both single-agent and multi-agent commerce scenarios.