Google launches A2A agent-to-agent protocol with 50 partners

Google listened to most of the critics around MCP and launched a new protocol called A2A. On the surface this protocol is complementary to MCP, but clearly Google is going to compete with Anthropic.

A2A enables agent to talk with each other via multi-modals. In A2A agents share what they can do with json cards.

Quite impressive that A2A launches with 50 partners.

It's based on these principles:

• Agentic Collaboration: Agents team up naturally, even if they don’t share the same memory or tools.
• Built on HTTP, SSE, and JSON-RPC for easy integration.
• Secure by Default
• Handles long running jobs like deep research with real-time updates.
• Multimodal

How it works

Components:

• Agent Cards: agents advertise their capabilities with json agent cards, defined in /.well-known/agent.json.
• Server: agent exposing an HTTP endpoint, with a json specification.
• Client: an 👉 application 👈 or agent that consumes the A2A services, sending request to task/send.
• Task: a client initiates a task by sending a message (tasks/send or tasks/sendSubscribe). Tasks have unique IDs and progress through states (submitted, working, input-required, completed, failed, canceled).
• Message: these are like the gpt messages the client (role: "user") and the agent (role: "agent"). Messages contain Parts.
  • Part: The fundamental content unit within a Message or Artifact. Can be TextPart, FilePart (with inline bytes or a URI), or DataPart (for structured JSON, e.g., forms).
  • Artifact: Represents outputs generated by the agent during a task (e.g., generated files, final structured data). Artifacts also contain Parts.

The protocol also also implement Streaming and PushNotifications.

To better understand how it works here's a python AgentCard implementation:

👉 Important to notice that A2A works also with application, which means the war of interoperability between hyperscalers is on!

Link to A2A: https://github.com/google/a2a.