Loading…
Loading…
Google's A2A (Agent-to-Agent) Protocol is a communication standard, not an agent itself. An AI agent is the autonomous worker; A2A is the language agents use to talk to each other. Understanding this distinction is critical for architects building multi-agent systems—A2A enables interoperability between agents from different vendors and platforms.
Written by Max Zeshut
Founder at Agentmelt
An AI agent is an autonomous system that plans, reasons, uses tools, and executes tasks. It has its own capabilities, knowledge, and purpose. Examples: a sales agent that handles outreach, a support agent that resolves tickets, a coding agent that fixes bugs. Each agent operates independently but may need to collaborate with other agents.
A2A (Agent-to-Agent) is Google's open protocol that standardizes how AI agents discover each other, negotiate tasks, exchange messages, and share results—regardless of which platform or vendor built them. A2A defines Agent Cards (capability descriptions), task lifecycle management (submitted → working → completed), and message formats. Think of it as HTTP for agents: a universal communication standard.
Without A2A, every agent-to-agent integration requires custom code—an O(n²) problem as agent count grows. A2A makes integration O(n): each agent implements the protocol once and can communicate with any other A2A-compatible agent. This enables multi-vendor ecosystems where a Salesforce agent, a custom support agent, and a Google Workspace agent collaborate seamlessly.
MCP (Model Context Protocol, by Anthropic) standardizes agent-to-tool communication. A2A standardizes agent-to-agent communication. They're complementary layers: an agent uses MCP to connect to its tools (databases, APIs, services) and A2A to communicate with peer agents. A well-architected multi-agent system uses both.
No. A2A is specifically for multi-agent communication. If you have one agent that handles all your tasks, A2A adds no value. Consider A2A when you have multiple specialized agents that need to collaborate, when you're integrating agents from different vendors, or when you want to participate in multi-agent ecosystems.
A2A was released in April 2025 and is gaining adoption, with support from major platforms including Salesforce, SAP, and several AI agent vendors. It's suitable for early production use but the ecosystem is still maturing. For new multi-agent architectures, designing with A2A support is a good investment. For existing single-agent deployments, there's no urgency to adopt.