Agent2Agent (A2A) Standard: Why Microsoft Backing Google Matters

On May 7, 2025, something surprising happened in the world of AI. Microsoft announced it would adopt Google’s Agent2Agent (A2A) protocol.

This protocol is a new, open standard that helps smart software—called AI agents—talk to each other, even if they run on different platforms or clouds.

Why is this a big deal? Well, Microsoft and Google are usually strong rivals, especially in cloud services and artificial intelligence.

Now, they’re agreeing to use the same set of rules for how their AI tools communicate. It’s like two major phone companies agreeing to use the same network so all their customers can call each other, no matter who they pay.

By supporting A2A, Microsoft will add this protocol to its own tools, including Azure AI Foundry and Copilot Studio. These tools help developers build AI-powered apps and services. Microsoft also joined the official A2A working group on GitHub, where companies and developers help improve the standard together.

This decision isn’t just about technology—it’s a sign that the AI industry is changing. Businesses and developers want their AI tools to work together smoothly, even if they come from different companies.

Why AI Agents Need a Common Language

AI agents are getting smarter and more useful every day. These agents are software programs that can take actions, solve problems, and make decisions on their own.

Microsoft is deeply involved in this area, with over 10,000 organizations already using its new Agent Service and more than 230,000—including 90% of Fortune 500 companies—building with Copilot Studio.

But even with all this growth, there’s a big problem: these agents often can’t talk to each other.

That’s because many of them are stuck inside their own company’s systems. They’re built to work with just one cloud platform or one group of tools. This situation is called a “silo,” and it’s like having every app on your phone speak a different language. Without a shared way to communicate, these agents can’t work together to complete bigger, more complex jobs.

For example, imagine trying to book a business trip where one AI handles your calendar, another finds flights, and another approves expenses—but none of them can share info. That’s what happens today when agents are locked in silos.

To fix this, AI agents need a shared language. That means setting clear rules and standards so any agent, no matter who made it, can connect and work with others.

This idea is at the heart of the new A2A protocol. It helps agents talk to each other across different apps, clouds, and companies.

What Exactly Is Agent2Agent?

Agent2Agent (A2A) provides a shared language that allows agents—no matter who built them or where they run—to work together. This means an agent running in one cloud or built with one framework can team up with another agent built differently.

The goal is to make intelligent software more connected and more useful in real-world tasks that cross apps, platforms, and vendors.

The Agent Card: How Agents Discover Each Other

At the center of A2A is something called the Agent Card. This is a machine-readable file that acts like a business card for an AI agent. It lists what the agent can do, what kinds of inputs and outputs it handles, how to contact it, and what kind of authentication it needs.

Developers publish Agent Cards in a standard location online so other agents can discover them automatically. This makes it possible to build systems where agents can find the best teammate for the job in real time—without hard-coding anything.

Communication: Using Familiar Web Standards

A2A is designed to be easy to adopt. It runs on basic web technologies like HTTP and JSON, which most developers already use.

Agents can act as servers by exposing endpoints that follow the Agent2Agent protocol. They can also be clients that send tasks to other agents.

Every task has a unique ID and moves through a clear life cycle, including states like submitted, working, input-required, completed, or failed. This structure helps agents coordinate even when jobs are complex or long-running.

Messaging and Streaming: Real-Time Teamwork

When agents talk, they send messages made of different parts. These parts might be plain text, structured data, or even files.

For tasks that take time, A2A supports live updates using streaming methods like Server-Sent Events. An agent can subscribe to updates and receive ongoing progress reports.

A2A also allows push notifications, so agents can send alerts to specific webhooks as soon as something important happens. This kind of back-and-forth makes multi-agent teamwork feel responsive and coordinated.

Security: Built-In and Enterprise-Ready

Security is a core part of A2A, not an afterthought.

The protocol includes authentication and authorization tools that ensure agents can verify who they’re talking to and what they’re allowed to do.

Agent Cards play a role here too, listing security requirements up front. This design makes A2A safe enough for enterprise use, even when agents are communicating across cloud providers or organizational boundaries.

Design Principles: Why Agent2Agent Is Built to Last

A2A was built to be open, flexible, and future-proof. The full specification is available on GitHub, and dozens of tech companies have already contributed to it.

The protocol is designed to handle a wide range of content—from files and forms to images and streaming audio—and it doesn’t require agents to share their internal logic. That means developers can build useful agents while keeping their proprietary tech private.

By relying on familiar tools and focusing on practical needs like security, discovery, and asynchronous workflows, A2A lowers the barrier to entry for anyone looking to build in the multi-agent future.

Microsoft’s Motives – If You Can’t Beat the Standard, Join-and-Guide It

Experts speculate that Microsoft’s announcement is a calculated move to stay at the center of the AI conversation.

Rather than fight a rising open standard, Microsoft chose to join and shape it. This decision shows how strategic cooperation at the infrastructure level can protect market position, attract customers, and future-proof platform investments.

Customers Are Demanding Interoperability

One major reason for Microsoft’s adoption of A2A is simple: its customers asked for it.

Enterprises building AI systems no longer want closed ecosystems. They want agents that can reach across company lines, tools that work across clouds, and workflows that don’t stop at platform borders. Microsoft put it plainly—interoperability is no longer optional.

By adopting A2A, the company is directly responding to this demand and signaling that it won’t let vendor lock-in define its AI future.

Open Standards, but on Microsoft’s Terms

Supporting A2A also allows Microsoft to maintain its relevance in a world that’s shifting toward openness. CEO Satya Nadella has called open agent protocols like A2A key to enabling the “agentic web,” where smart systems are connected and collaborative by default.

Rather than resist, Microsoft is positioning itself as a leader in this next phase of software—one that is designed to be observable, adaptive, and open from the ground up.

Agent2Agent Integration in Azure AI Foundry

By integrating A2A into Azure AI Foundry, Microsoft gives developers the ability to build multi-agent workflows that include both internal and external tools. These workflows can span data silos, business units, and even cloud providers.

A Foundry-built agent could now delegate parts of a task to third-party agents and still deliver results under existing service-level guarantees. That flexibility makes Microsoft’s platform more useful without giving up control or security.

A2A-Ready Copilots in Copilot Studio

In Copilot Studio, A2A support unlocks broader functionality.

Agents built in Studio can now invoke external agents—no matter what platform they were built on or where they’re hosted. This turns the Copilot into more than just a Microsoft-focused assistant. It becomes a smart coordinator, able to tap into a whole ecosystem of agents to get things done.

This approach supports Microsoft’s “Copilot for Everything” vision, where one assistant can manage an entire task flow, even if parts of that flow happen outside Microsoft’s walls.

Real Examples and Developer Support

To make adoption easier, Microsoft is showing how A2A works in practice using tools developers already know. Semantic Kernel, its open-source SDK for building AI agents, now works with A2A.

Microsoft has published integration samples in Python and .NET, demonstrating how a single agent can connect with specialized sub-agents—for example, one that handles currency exchange and another that plans travel activities. These real-world use cases show how developers can build rich, cross-agent applications with minimal setup.

Where Agent2Agent Fits with Other Standards (MCP, AGNTCY)

As AI systems evolve, multiple open standards are emerging to support more connected and capable agent ecosystems. Google’s A2A protocol plays a central role in this movement, but it works best when viewed alongside other efforts like Anthropic’s Model Context Protocol (MCP) and the community-driven AGNTCY initiative.

MCP focuses on enabling agents to interact with external tools, APIs, and data. It standardizes how an agent accesses the services it needs to perform tasks—whether it’s querying a database or calling a third-party API. It’s already backed by key players like Microsoft, Google, and OpenAI. In contrast to A2A, which governs communication between agents, MCP manages how agents talk to their environment. Used together, they support a layered agent architecture: an agent might use MCP to gather data, then use A2A to pass that data to another agent.

Comparative Overview: A2A vs. MCP

To further clarify the distinctions and complementarities, the following table provides a comparative overview of Google’s A2A and Anthropic’s MCP:

AGNTCY takes a broader view, aiming to build an “Internet of Agents.” This initiative, supported by companies like Cisco and LangChain, focuses on agent discovery, evaluation, and network-wide interoperability. It introduces a shared schema for describing agents, a protocol for secure interaction, and a searchable directory—essentially laying the groundwork for a global marketplace of interoperable agents.

While A2A, MCP, and AGNTCY serve different functions, they aren’t competing—they’re complementary. A2A handles agent-to-agent collaboration, MCP powers agent-to-tool execution, and AGNTCY supports scalable agent discovery and coordination. Together, they define a growing protocol stack for AI systems.

Still, while the standards may cooperate, the platforms supporting them do compete. Google, Microsoft, and Anthropic each provide their own SDKs and orchestration layers, and the long-term success of these protocols may depend on which ecosystems deliver the best tools, integrations, and developer experience. In this new phase of AI, openness is just the starting point—operational value will determine who leads.

Who Wins Right Now?

Microsoft’s support for A2A doesn’t just change how AI systems are built—it also shifts who benefits the most from this new standard. Developers, enterprises, and the broader market each stand to gain, but in different ways. A2A is not just a technology upgrade—it’s a restructuring of how value is created and shared across the AI ecosystem.

1. Developers Get Interoperability and New Reach

For developers, A2A opens the door to a more flexible and inclusive way to build software. I

nstead of needing to code one-off integrations between specific agents or platforms, they can now rely on a shared communication standard. This reduces complexity and speeds up development. Agents no longer need to live inside the same cloud, app, or vendor ecosystem to work together.

For example, a calendar agent built on Microsoft’s platform could coordinate directly with a document agent hosted by Google—all through A2A.

But the biggest change is about accessibility. Small teams or solo developers can now focus on building niche, high-performing agents without having to own the entire workflow. As long as their agents expose capabilities via an Agent Card, they can be plugged into much larger systems. This mirrors how APIs allowed startups to build focused tools that plugged into broader platforms.

With A2A, developers don’t need to compete with tech giants across the whole stack—they can specialize, connect, and thrive.

2. Enterprises Unlock Smarter, Cross-Vendor Workflows

For businesses, A2A makes AI more practical and powerful.

Companies often use tools from multiple providers—internal copilots, third-party services, and legacy systems all under one roof. A2A makes it possible to connect these parts in ways that weren’t feasible before. Enterprises can now build multi-agent workflows that span clouds and vendors while still enforcing governance, security, and service-level standards.

This means more automation for complex tasks, fewer manual handoffs, and smoother coordination between departments and systems. Enterprises can treat agents like digital teammates, assigning them parts of larger tasks and expecting real results in return.

The market seems ready for this shift. The AI agent market is projected to grow dramatically—from $7.84 billion in 2025 to over $52 billion by 2030—and A2A is a key enabler of that growth. With more than 65% of organizations already experimenting with agent technologies, the appetite for standards-based solutions is clear.

3. Microsoft Strengthens Its Ecosystem

Microsoft gains on several fronts. By adopting A2A, it stays ahead of the demand for open solutions while still anchoring users in its ecosystem. Azure AI Foundry and Copilot Studio become more attractive to developers who want flexibility without giving up enterprise-grade tools. A2A support makes it easier for customers to use external agents without leaving Microsoft’s stack.

Even more importantly, Microsoft is adding layers of value on top of A2A. Through features like Semantic Kernel, Entra for security, and deep audit logging, Microsoft offers not just access, but governance, safety, and scalability. These enterprise-grade additions position Microsoft’s platforms as the “professional” environment for multi-agent systems—where reliability, compliance, and control are non-negotiable.

The Market Benefits from Open Foundations

A2A also rebalances competition across the industry. It weakens the grip of closed platforms and encourages a broader, more diverse marketplace of AI agents.

With basic communication standardized, the next wave of competition moves up the stack—to developer tools, integrations, security layers, and agent performance. Much like cloud providers compete on services layered over open infrastructure like Kubernetes, AI platforms will now compete on how well they support building, managing, and deploying agents using shared protocols like A2A.

SmythOS: Operationalizing Open Standards

SmythOS is playing a key role in bringing open agent protocols to life.

As an early supporter of the Model Context Protocol (MCP), SmythOS has shown a strong commitment to interoperability. Its platform focuses on helping developers and organizations manage and orchestrate multi-agent systems across vendors and standards.

SmythOS works directly with other ecosystem players to ensure compatibility and shared progress toward an open Internet of agents. Where protocols like A2A and MCP define the rules of engagement, SmythOS provides the operational layer—turning those rules into secure, scalable, and production-ready workflows.

Final Words: A New Playbook for Coopetition

Microsoft’s endorsement of Agent2Agent shows that even fierce rivals can align when the foundation of a market is at stake. The future of AI will be shaped by open protocols, shared infrastructure, and systems designed to work across platforms—not by isolated tools locked inside vendor silos. The companies that win will be those that cooperate on standards but compete on execution, security, and experience.

For developers and enterprises, this is a moment of opportunity. Building AI agents that talk to each other is no longer a stretch goal—it’s a strategic advantage. But making that interoperability work in practice requires more than just a protocol. It requires a system to design, deploy, and manage complex agent workflows across clouds and vendors.

That’s where SmythOS comes in. As a platform committed to open standards like MCP and aligned with the goals of A2A, SmythOS helps you operationalize this new generation of AI. It provides the orchestration, visibility, and infrastructure you need to build agentic systems that are not just connected—but also secure, scalable, and enterprise-ready.

If you’re planning your AI roadmap, now is the time to act. Use open protocols. Design for interoperability. And consider platforms like SmythOS to turn those ideas into reality—because tomorrow’s most capable systems won’t be built in isolation. They’ll be built together.

Article last updated on: Last updated: May 8, 2025