Agent-to-Agent Protocol (A2A)

Definition

The Agent-to-Agent Protocol (A2A) is an open protocol developed by Google that enables AI agents built by different companies to discover, communicate, and collaborate with each other. While MCP connects AI models to tools and data sources, A2A connects AI agents to other AI agents - enabling multi-agent workflows where specialized agents work together to complete complex tasks.

Google announced A2A in April 2025 with backing from over 50 technology partners. The protocol addresses a growing problem: as organizations deploy multiple AI agents from different vendors, those agents need a standard way to talk to each other. Without A2A, each agent operates in isolation, unable to delegate tasks or share context with agents built on different platforms.

In the ecommerce context, A2A enables scenarios where a user’s personal shopping agent communicates with a merchant’s customer service agent, which in turn coordinates with inventory and fulfillment agents - all seamlessly, even though each agent may be built by a different company using different AI models.

Why It Matters

A2A matters because the future of AI commerce is not a single agent doing everything. It is a network of specialized agents collaborating. A shopping agent might be great at understanding user preferences but needs to hand off to a merchant’s agent for inventory checks, and to a logistics agent for delivery estimates.

For merchants, A2A opens the possibility of deploying AI agents that can participate in a broader ecosystem. A merchant’s product recommendation agent could be discovered and consulted by any A2A-compatible shopping assistant, extending the merchant’s reach into AI-driven channels they do not directly control.

The protocol also signals the competitive dynamics of the AI infrastructure layer. Google’s A2A and Anthropic’s MCP are complementary but represent different visions. MCP is about connecting AI to tools and data. A2A is about connecting AI to other AI. Together, they form the communication backbone of the emerging agent economy.

For the ecommerce industry specifically, A2A could reshape how complex shopping journeys work. Price comparison, product research, purchase coordination, returns processing - each step could be handled by a specialized agent, with A2A handling the handoffs between them.

How It Works

A2A operates around several key concepts:

Agent Cards are JSON metadata files that describe what an agent can do. Each agent publishes a card at a well-known URL (typically /.well-known/agent.json) that lists its capabilities, supported interaction modes, and authentication requirements. This is how agents discover each other.

Tasks are the fundamental unit of work in A2A. One agent sends a task to another, and the receiving agent processes it and returns results. Tasks can be short-lived (a quick query) or long-running (a complex research workflow), and they support streaming for real-time updates.

Messages and Parts handle the content exchanged between agents. Messages can contain multiple parts - text, structured data, files, or references. This flexibility allows agents to exchange rich information beyond simple text strings.

Collaboration Modes define how agents interact. A2A supports request-response patterns for simple queries, streaming for ongoing updates, and push notifications for asynchronous workflows where an agent needs time to complete a task.

A practical ecommerce scenario: a user asks their AI assistant to find the best deal on a specific laptop. The assistant’s agent discovers merchant agents via their Agent Cards, sends product query tasks to multiple merchant agents simultaneously, receives responses with pricing and availability, and synthesizes the results for the user. Each merchant agent handles the query using its own tools and data - possibly through MCP connections to its inventory system - and returns results through A2A.

Related Terms

• Model Context Protocol (MCP) - Connects AI models to tools and data, complementing A2A’s agent-to-agent communication
• Tool Use - The capability A2A agents use internally when processing tasks
• Agentic Commerce - The commerce paradigm that multi-agent collaboration enables
• Agentic Commerce Protocol (ACP) - Shopify’s commerce-specific protocol that could work alongside A2A