Announcing the Agent2Agent Protocol (A2A)
đhttps://shre.ink/Agent-2-Agent-Protocol
Google launched Agent2Agent (A2A), a new open protocol that enables AI agents from different developers and frameworks to communicate and collaborate, with backing from 50+ tech and service giants, including Salesforce, SAP, and PayPal.
1. A New Era of Agent Interoperability
A2A is an open protocol that enables AI agents from different vendors and frameworks to communicate and collaborate. As enterprises increasingly rely on autonomous agents for tasks like customer service, procurement, and planning, interoperability becomes essential to unlock productivity and reduce costs.
Backed by 50+ major tech and consulting partners, A2A allows agents to securely exchange data and coordinate actions across platforms, creating a standardized way to manage agents in complex enterprise environments. It complements protocols like Anthropicâs MCP and draws on Googleâs experience in building large-scale, multi-agent systems.
The goal: a universal framework that empowers agents to work together, regardless of who built themâdriving innovation, efficiency, and scalable automation.
2. A2A Design Principles
A2AÂ follows five core principles:
Agent-native collaboration: Supports natural, unstructured interactions without requiring shared memory or tools.
Built on open standards: Uses HTTP, SSE, and JSON-RPC for easy integration with existing IT systems.
Enterprise-grade security: Includes robust authentication and authorization, aligning with OpenAPI standards.
Handles long-running tasks: Suitable for both quick and complex tasks, offering real-time updates and feedback.
Modality agnostic: Supports communication across multiple formats, including text, audio, and video.
These principles ensure A2A is flexible, secure, and future-proof for enterprise-scale, multi-agent AI ecosystems.
3. How A2A Works
A2A enables a client agent to delegate tasks to a remote agent, who acts on them to provide results. The protocol includes several essential components:
Capability discovery: Agents use a JSON-based âAgent Cardâ to advertise what they can do, helping client agents choose the right collaborator.
Task management: Agents interact through structured âtaskâ objects, which have a defined lifecycle and may produce âartifactsâ as output.
Collaboration: Agents exchange messages to share context, user instructions, responses, or artifacts throughout the task.
User experience negotiation: Messages include âpartsâ with content types (e.g., image, video, form), allowing agents to adapt to the userâs UI capabilities.
Together, these features enable flexible, multi-modal agent collaboration focused on completing tasks efficiently.