Agent2Agent (A2A) Protocol
Introduction:
The rapid advancement of AI has ushered in a new era of intelligent systems, where autonomous agents are no longer just experimental but are being deployed at scale across industries. As these agents grow in complexity and number, seamless communication between them becomes essential. To address this, Google introduced the Agent2Agent (A2A) Protocol—a structured approach designed to facilitate efficient, reliable, and standardized communication among AI agents.
This protocol emerges as part of the broader evolution in AI infrastructure, where new processes and frameworks are continuously being developed to meet real-world demands. A2A enables agents to collaborate, delegate tasks, and share context—paving the way for more advanced, multi-agent systems capable of solving complex problems in dynamic environments.
Approach:
Fig.1. A2A Flow
As illustrated in the diagram, the user initiates a request through an application. The application forwards this request to an intelligent agent (Agent 1). During processing, Agent 1 identifies the need for additional context or data that it does not possess. Instead of redundantly fetching or recalculating the information, Agent 1 communicates with another agent (Agent 2) that already holds the required knowledge. By leveraging Agent 2’s capabilities via the Agent2Agent (A2A) Protocol, Agent 1 can quickly access the necessary data, respond more efficiently, and significantly reduce processing time and resource consumption.
Benefits:
Discovery:
Agents can dynamically identify and locate other agents with the necessary capabilities or data. This enables more flexible and scalable multi-agent ecosystems.
Negotiation:
Agents can communicate to reach agreements on how to share resources or divide tasks. This promotes efficient and autonomous decision-making in distributed systems.
Task Management:
A2A allows agents to delegate, accept, or coordinate tasks based on their availability and specialization. This ensures optimal task distribution and load balancing.
Collaboration:
Agents can work together by exchanging context, insights, and progress updates in real-time. This leads to more intelligent, cooperative behavior across complex workflows.
References:
https://developers.googleblog.com/en/a2a-a-new-era-of-agent-interoperability/
https://www.microsoft.com/en-us/microsoft-cloud/blog/2025/05/07/empowering-multi-agent-apps-with-the-open-agent2agent-a2a-protocol/