If your AI agents can’t talk to each other, you’re paying for a fleet of cars with no roads between them.
Every enterprise AI stack has the same coordination problem
Orchestrating AI agents across different vendors today means custom glue code, brittle handoffs, and hours of integration work every time a new tool enters the stack. There is no shared language — until now.
Google shipped a protocol, not just another product
[AINews] Google’s Agent2Agent Protocol (A2A) defines a structured communication layer where AI agents exchange tasks, pass messages, and return artifacts — without human intervention at each handoff. You point your orchestration layer at an Agent Card (a standardized identity file), define a Task, and the protocol handles the channel between agents, including streaming, push notifications, and enterprise auth. The output is a completed Artifact: a file, a decision, a structured result — whatever the downstream agent was built to produce.
The teams building multi-agent pipelines feel this first
- AI engineers integrating third-party agents who need a standard handoff contract instead of custom API wrappers for every vendor
- Enterprise architects designing agent workflows who need audit trails and auth that survive a security review
- Product leads at SaaS companies who need to connect their AI feature to partner tools without a six-week integration sprint
The protocol launched with 50+ named partners, which means real connectors exist on day one rather than a promise of future compatibility.
Anthropic’s MCP just got a peer, not a replacement
Google explicitly designed A2A to complement Anthropic’s Model Context Protocol: MCP handles tool use and context, A2A handles agent-to-agent coordination at a higher level. With both protocols gaining major backing inside the same month, the multi-agent infrastructure layer is consolidating faster than most enterprise teams have planned for.
What you can do with it today
- Route a research task from one agent to a specialized summarization agent automatically
- Define reusable Agent Cards to standardize how your internal agents identify themselves
- Build cross-vendor pipelines using the open draft specification without waiting for SDK lock-in
- Test agent coordination flows using Google’s Agent Development Kit reference implementation
Pricing not listed — check our directory.
The honest gap: the spec is still a draft
The specification is not finalized, which means production implementations built today may need to absorb breaking changes before the protocol stabilizes.
The alternatives worth knowing
Anthropic’s MCP covers the tool-use layer that A2A sits above, making them complementary rather than competing choices. Microsoft’s AutoGen and LangGraph both offer agent orchestration frameworks, but neither proposes an open cross-vendor protocol with this level of partner adoption.
The agent coordination layer is becoming infrastructure, not a feature
If multi-agent pipelines are on your 2025 roadmap, A2A is the spec your architecture decisions will be measured against. We cover tools like this every Friday — subscribe here and we’ll send the best ones straight to you.