Recently open-sourced by Google, the Agent2Agent protocol is now part of the Linux Foundation, along with its accompanying SDKs and developer tools.
The Agent2Agent protocol will be the cornerstone of a wider Agent2Agent project formed by Google, AWS, Cisco, Microsoft, and others. The project aims to foster interoperability for AI agents and break down the silos that are limiting collaboration between them, says the company.
By providing a common language for AI agents to discover each other’s capabilities, securely exchange information, and coordinate complex tasks, the A2A protocol is paving the way for a new era of more powerful, collaborative, and innovative AI applications.
Using the Agent2Agent protocol, agents can discover each other’s capabilities, negotiate how to interact, and collaborate securely on long-running tasks. The protocol is particularly focused on preserving each agent’s internal state, including its prompt.
The protocol is based on JSON-RPC 2.0 over HTTP and uses server-sent events for real-time streaming between agents. Agents know about each other through “agent cards” that describe agent capabilities and provide connection info. In the future, agent cards will include also authorization schemes and optional credentials. Other areas of future development include client-initiated interactions and dynamic UX negotiation within tasks, such as adding audio/video formats after the initial negotiation phase, i.e. after the agents have started their conversation.
According to Google, the Agent2Agent protocol has seen significant adoption, with over 100 companies supporting it. Since its original announcement, the protocol has raised some controversy due to its overlap with Anthropic’s Model Context Protocol (MCP).
Reddit commenter Impressive-Owl3830 expressed concern that this overlap might prevent the two protocols from coexisting, with MCP already having “taken off”. Another redditor, Specialist_Apricot74, noted this announcement “puts to rest the threat of the triple E threat (Embrace, Extend, Extinguish)” and could help Agent2Agent to differentiate itself from MCP by reducing its overlap and specializing in at least one task that MCP cannot do.
Google says Agent2Agent is ideal when agents are developed and deployed independently, come from different teams, require dynamic discovery and composition, and need to support third-party integration or frequent changes, such as adding or removing agents at any time.
If you are interested in Agent2Agent, a great starting point is Google’s unofficial Python Notebook, which illustrates how you can set up a system with three agents, one searching the web for current trending topics, another performing deep analysis, and the last orchestrating the first two to provide insights.
