Agent2Agent (A2A): How AI Agents From Different Vendors Work Together

Yes, in most cases your AI agents can work together even if you buy them from different vendors, and the reason is two open protocols rather than one. The Model Context Protocol (MCP) standardizes how a single agent connects to your tools and data. The Agent2Agent protocol (A2A) standardizes how separate agents discover each other and hand off work. Both are open, both are backed by most of the major AI vendors, and as of late 2025 both sit under the same neutral governance body, the Linux Foundation's Agentic AI Foundation. If you are picking agent vendors and worried about getting locked into one company's ecosystem, this is the part of the market you actually need to understand, and it is simpler than the acronyms make it look.

If you want a multi-agent system architected on these open standards from day one, that is exactly what our generative and agentic AI architecture work is built around.

Will AI agents from different vendors actually work together?

Increasingly, yes, and it is not a hypothetical anymore. A year ago, "agent interoperability" was a slide in a vendor pitch deck. By 2026 it is a working standard with a growing list of companies that have implemented it in production. The Agent2Agent protocol had more than 150 organizations supporting it by its one-year anniversary in April 2026, up from 50 at its April 2025 launch, and it is already integrated into Microsoft Azure AI Foundry and AWS Bedrock, with live deployments in supply chain, financial services, insurance, and IT operations.

That does not mean every agent works with every other agent automatically. It means the plumbing exists, and vendors are adopting it fast enough that "does this vendor support open agent standards" is now a fair, answerable question to put in front of any sales team, the same way you would ask about single sign-on or an export API a decade ago.

What is the Agent2Agent (A2A) protocol, in plain terms?

A2A is a way for one AI agent to find another AI agent, understand what it can do, and hand it a piece of work, regardless of which company built either agent or which underlying model powers it. Google originally built and launched A2A in April 2025 with support from more than 50 technology and consulting partners. Two months later, Google donated the protocol to the Linux Foundation specifically so no single company would control its direction.

Technically, A2A works through two simple ideas:

• Agent Cards. Every A2A-compatible agent publishes a structured description of itself, typically at a predictable web address, that lists what it can do, what kinds of input it accepts (text, images, audio), and which protocols it speaks. Think of it as a resume an agent hands another agent before they start working together.
• Tasks. Once two agents agree to work together, the actual work is wrapped in a "Task" with a defined lifecycle: submitted, working, completed, or failed. Tasks can stream updates back in real time, so the requesting agent (or the human watching it) can see progress rather than waiting on a black box.

That is the whole idea. One agent reads another's card, decides it is the right tool for the job, and sends it a task with clear inputs and expected outputs. No custom integration code, no vendor-specific API to learn, because both sides speak the same protocol.

How is A2A different from MCP?

This is the question that trips up most buyers, so it is worth being direct about it: A2A and MCP are not competing standards, they operate at different layers, and most serious agent deployments end up using both.

Put simply: MCP is how an agent reaches down into your systems. A2A is how an agent reaches sideways to another agent. A single useful workflow, say a sales agent that qualifies a lead and then hands it to a scheduling agent, typically needs both: MCP so each agent can touch the CRM and calendar it needs, and A2A so the two agents can pass the lead to each other cleanly.

The pace of adoption on both sides has been fast. MCP launched in November 2024, and within four months OpenAI had adopted it across its Agents SDK, Responses API, and ChatGPT desktop app. Google DeepMind added Gemini support the following month, and Microsoft and GitHub joined MCP's steering committee and shipped Windows 11 support by May 2025. By its one-year mark, MCP was seeing roughly 97 million monthly SDK downloads and more than 10,000 active servers, a figure that had grown past 110 million monthly downloads by April 2026.

Why did Google hand A2A to the Linux Foundation?

Because a protocol that only one company controls is not really a neutral standard, it is that company's roadmap with an open-source license attached. Jim Zemlin, the Linux Foundation's executive director, put it directly when the donation was announced: "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."

The founding steering committee reflects that intent. It includes engineers from AWS, Cisco, Google, IBM Research, Microsoft, Salesforce, SAP, and ServiceNow, which is to say most of A2A's own commercial competitors sit on the committee that decides where the protocol goes next. Darrel Miller, a Microsoft Partner API Architect, made the buyer-relevant point plainly: "For AI agents to be effective in enterprise environments, they need to operate across organizational boundaries." A protocol owned by one vendor cannot credibly promise that.

The same logic played out with MCP. In December 2025, Anthropic, the company that built MCP, donated it to a new Linux Foundation directed fund called the Agentic AI Foundation (AAIF). OpenAI donated a related project of its own (AGENTS.md, a convention for instructing coding agents), and Block donated its open-source Goose agent framework. That is the detail most coverage of this space misses: as of late 2025, MCP and A2A, built by rival companies, both sit inside the same neutral governance structure. The AAIF had grown to more than 170 member organizations by April 2026.

How much has agent interoperability actually grown?

Enough that it is no longer a bet on the future, it is a current baseline you can check against any vendor you are evaluating. Here is the one-year picture, April 2025 to April 2026:

• A2A: 50 organizations at launch to 150-plus a year later, with 22,000-plus GitHub stars on the core repository and five production-ready SDKs (Python, JavaScript, Java, Go, .NET).
• A2A v1.0, released in early 2026, added multi-protocol support and enterprise-grade multi-tenancy, and is now built into Azure AI Foundry and AWS Bedrock.
• A related payments extension, the Agent Payments Protocol (AP2), already has 60-plus supporting organizations, which matters if you ever want an agent to complete a transaction on your behalf.
• MCP: roughly 97 million monthly SDK downloads around its one-year mark, growing past 110 million by April 2026.
• The Agentic AI Foundation, the neutral home for both protocols plus AGENTS.md (60,000-plus open-source projects using it) and Goose (29,000-plus GitHub stars), reached 170-plus members by April 2026.

None of this guarantees your specific vendor supports either protocol well, or at all. What it tells you is that "open agent standards" moved from an experiment to infrastructure in about twelve months, roughly the same speed cloud APIs standardized a decade earlier. That speed is itself useful information when you are deciding whether to bet on a closed platform today.

What does "agent interoperability" actually mean for your business?

Concretely, it means you can build (or buy) agents that specialize, rather than needing one vendor's all-in-one platform to do everything adequately. A support agent from one vendor can hand an escalation to a different vendor's specialist agent. A research agent built in-house can pull structured data from a third-party agent without a custom integration project. You are not required to standardize on a single agent framework across your whole business, which is the trap a lot of companies fell into with early automation platforms.

It also changes how you should think about switching costs. Before open agent protocols, replacing one vendor's agent meant rebuilding every custom integration that connected it to your other systems and other agents. With A2A and MCP genuinely in place, swapping a vendor is closer to swapping a SaaS tool that happens to speak a standard API: still work, but not a rebuild from zero.

How to avoid vendor lock-in when picking AI agent vendors

Use this as a short checklist in any agent vendor evaluation:

1. Ask directly, in writing. "Do you support MCP for tool and data access? Do you support A2A for agent-to-agent handoffs?" A vague "we have integrations" answer is not the same as protocol support.
2. Check the governance, not just the marketing. A vendor that says "we built our own agent protocol" is telling you they are the single point of control. A vendor that points to the Agentic AI Foundation or the A2A GitHub org is telling you the standard outlives them.
3. Ask for data portability separately. Open communication protocols do not automatically mean you can export your data, your agent configurations, or your workflow history. Get that in the contract, not implied by the protocol.
4. Prototype a real handoff. Before committing, test one actual A2A handoff between the vendor's agent and something you already run, even a simple one. If it takes a custom integration project to make basic interoperability work, the "support" is marketing, not architecture.
5. Prefer modular over monolithic. A vendor that expects you to run your entire agent stack on their platform is a bigger lock-in risk than one whose agents can sit alongside agents from other vendors, connected through A2A.

What A2A and MCP do not solve

It is worth being honest about the limits here, because overselling interoperability is exactly how buyers get burned twice. Open protocols standardize communication, not everything else that creates lock-in. They do not standardize pricing, hosting, uptime guarantees, or how easy it is to export your historical data if you leave a platform. They also do not guarantee quality: an agent that speaks A2A correctly can still be unreliable at the actual task. Interoperability tells you agents can talk to each other, not that talking to each other is enough to trust them with real decisions. That trust still comes from evals, guardrails, and a human in the loop on anything consequential, the same fundamentals that apply to any agent regardless of which protocol it speaks.

Where this is already showing up in real deployments

The Linux Foundation's own reporting on A2A's first year points to production use in supply chain coordination, financial services, insurance claims workflows, and IT operations, the kind of work that has always involved handing a task between specialized systems or specialized people. That is not a coincidence. Multi-agent handoffs are most valuable exactly where a single generalist agent would be worse than a set of specialists that know when to pass work along, which is the same reason a business hires a support team instead of one person who does everything. If your business already thinks in terms of handoffs between departments, you already have the mental model for where A2A helps.

How to get started evaluating your agent stack

You do not need to become a protocol expert to buy correctly. Start by listing the agents you already use or are evaluating, and put one question next to each: does this vendor publicly support MCP, A2A, or both? For anything you build in-house, design new agents to speak these protocols from the start rather than retrofitting later, since retrofitting a proprietary integration into an open one is real engineering work you can avoid entirely by starting right. And when you are choosing between two otherwise similar vendors, treat open standards support as a tiebreaker with real weight, because it is one of the few signals that predicts whether you will still like this vendor in two years.

If you would rather have this designed and built for you, that is what we do. We architect multi-agent systems on open standards like A2A and MCP so the agents we build for you keep working together, and keep working with whatever you add next, without locking you into us or any single tool vendor. Book a free consultation and we will map out where agent interoperability actually matters for your business.