The Linux Foundation announced it will host the Agent2Agent (A2A) protocol, an open standard initially developed by Google and now supported by more than 100 technology companies for secure communication between AI agents. The adoption addresses one of AI’s most pressing challenges: enabling autonomous agents to discover each other, exchange information, and collaborate across different platforms and vendors.
What you should know: A2A creates a standardized communication layer that breaks down silos limiting multi-agent AI systems.
- The protocol uses AgentCards—JSON metadata documents that describe an agent’s purpose and provide access instructions via web URLs.
- A2A leverages widely adopted web standards including HTTP, JSON-RPC, and Server-Sent Events to ensure broad compatibility.
- Enterprise-grade security features include support for JSON Web Tokens (JWTs), OpenID Connect (OIDC), and Transport Layer Security (TLS).
The big picture: A2A enables a new era of AI productivity by allowing specialized agents to work together on complex tasks.
- As Antje Barth, an AWS principal developer advocate, explained: “Say you want to book a train ride to Copenhagen, then a hotel there, and look maybe for a fancy restaurant, right? You have inputs and individual tasks, and A2A adds more agents to this conversation, with one agent specializing in hotel bookings, another in restaurants, and so on.”
- The protocol allows agents to communicate, hand off tasks, and provide feedback to end users through coordinated workflows.
Who else is involved: Major technology companies are backing the A2A initiative alongside Google.
- Supporters include Amazon Web Services, Cisco, Microsoft, Salesforce, SAP, and ServiceNow.
- Jim Zemlin, executive director of the Linux Foundation, expects A2A to become “a cornerstone for building interoperable, multi-agent AI systems.”
How it works with other protocols: A2A is designed to complement Anthropic’s Model Context Protocol (MCP) rather than compete with it.
- MCP provides a standardized way for individual AI agents to access external tools, APIs, and data sources—acting as a “USB-C port for AI applications.”
- A2A focuses on horizontal communication between multiple agents, while MCP handles vertical connections between agents and tools.
- As AI company Clarifai explained: “These two protocols solve different parts of the communication problem: A2A focuses on how agents communicate with each other (horizontally), while MCP focuses on how a single agent connects to tools or memory (vertically).”
Putting protocols into practice: Real-world implementation combines both A2A and MCP for comprehensive agent functionality.
- When an IT support agent receives a ticket about slow application performance, it uses MCP to gather diagnostic data from monitoring tools.
- If issues span multiple domains like network, database, or application, the agent uses A2A to delegate investigation parts to specialized agents.
- Each specialized agent may then use MCP to access their relevant tools.
What they’re saying: Industry experts acknowledge both the potential and challenges ahead.
- “By joining the Linux Foundation, A2A is ensuring the long-term neutrality, collaboration, and governance that will unlock the next era of agent-to-agent powered productivity,” said Zemlin.
- Barth cautioned: “We’re still in early stages from a protocol and standardization perspective. And I don’t think we’re yet there to call; there’s just going to be one protocol to tackle all the use cases.”
- “Gartner says a third of all applications and enterprises will be powered by Agentic AI by 2028. So, there’s never been a better time for developers to start building, start learning,” Barth concluded.
Competitive landscape: A2A faces competition from other agent communication protocols.
- IBM’s Agent Communication Protocol (ACP), based on REST architecture, also has Linux Foundation support.
- The protocol standardization space remains fluid as different approaches compete for adoption.
- Mike Smith, Google staff software engineer, noted that A2A has evolved to make it easier to add custom extensions and assign unique identities to agents for improved governance and security.
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