Introduction

Imagine having multiple AI tools that not only help you individually, but also collaborate like a real team to solve problems faster, better, and more securely. This isn’t just a sci-fi dream—it’s what Google Cloud’s Agent2Agent (A2A) Protocol makes possible.

In 2025, Google made a major move: it donated the A2A protocol to the Linux Foundation, a neutral nonprofit project that supports the open development of the protocol. The A2A protocol is the result of a collaborative effort among industry leaders, led by Google and supported by companies like AWS, Microsoft, SAP, Salesforce, and ServiceNow. This donation has accelerated adoption by top players and enabled A2A to grow as a true cross-platform standard. The Agent2Agent protocol is a critical component in the AI ecosystem, enabling open, interoperable, and collaborative AI applications across vendors and platforms.

Whether you’re a beginner curious about AI or a pro building agent ecosystems, this blog will break down the A2A protocol so anyone can understand and benefit from it. A2A is also driving business transformation by empowering organizations to modernize and optimize their processes through agent-based systems.

1. What Is the A2A Protocol?

The Agent2Agent (A2A) protocol is an open standard that allows AI agents to talk, share information, and collaborate securely across different systems. As an open protocol for agent communication, A2A enables secure, interoperable interactions between AI agents across platforms, networks, and organizational boundaries. Open protocols like A2A are essential frameworks that facilitate structured, secure communication and collaboration among agents, regardless of their underlying platforms or vendors. It also acts as an interoperability layer, supporting seamless integration and collaboration between diverse AI systems from different vendors. It solves a critical problem:

Problem: AI agents are isolated. 
Solution: A2A enables agents from different vendors and ecosystems to work together using a shared language and structure.

Just like how Gmail can send emails to Yahoo or Outlook, A2A allows a chatbot from one company to communicate and collaborate with a tool or assistant from another. It’s a universal communication protocol for AI agents. A2A fosters an open and interoperable ecosystem where agents from different vendors can collaborate seamlessly.

By supporting the development of an interoperable ecosystem for AI agents, A2A empowers organizations to innovate and deploy collaborative AI solutions more efficiently.

2. The Significance of Google’s Donation to the Linux Foundation

In June 2025, Google Cloud officially handed over the Agent2Agent protocol to the Linux Foundation. This wasn’t just a symbolic gesture. It meant:

  • Open Governance: The protocol is now managed in a vendor-neutral way, under an open governance framework established by the Linux Foundation.
  • Trust and Transparency: Organizations can adopt A2A without worrying about vendor lock-in.
  • Faster Adoption: Open standards evolve faster through community driven development, with community input being essential for accelerating the development and ensuring the interoperability of the protocol.
  • Broad Support: Many industry leaders joined in after the donation, seeing it as a standard that could unify AI collaboration, with the broader community actively involved in shaping the protocol.

This shift has positioned A2A as a critical building block for the future of interoperable AI systems.

3. Why A2A Is So Important

Current Limitations

Most AI tools are like islands—most are traditionally disconnected systems. Vendor boundaries have historically limited collaboration and integration between AI tools, making it difficult for different platforms and vendors to work together seamlessly. They can do amazing things on their own, but they can’t easily work with other tools. This leads to:

  • Fragmented user experiences, as disconnected systems make it difficult for users to move seamlessly between tools.
  • Lots of custom integrations.
  • Missed opportunities for collaboration.

How A2A Changes the Game

With A2A, AI agents become a collaborative network:

  • They find each other using AgentCards, allowing agents to discover each other's capabilities.
  • They talk using messages and shared formats.
  • They complete tasks together and share results (artifacts), coordinating on complex tasks that require input from multiple systems.
  • They collaborate effectively by using a common protocol that enables intelligent agents built on different frameworks to work together seamlessly.

In short, A2A upgrades AI systems from single-player tools to multiplayer collaborators, helping to ensure agents can work together securely and efficiently across diverse platforms. A2A also supports cross platform collaboration, allowing agents built on different technologies to integrate and operate together for broader interoperability.

4. The Pillars of Agent2Agent: Making Agent Communication Work

To make agent collaboration reliable and productive, the A2A protocol defines a structured way for agents to introduce themselves, understand requests, exchange data, and deliver outcomes. The protocol provides the necessary structure to build agents that can operate and collaborate across multiple platforms and vendors, enabling scalable and interoperable agentic systems. Here are the five essential building blocks that power this system:

Agent Identity for AI Agents: The AgentCard

Each agent needs a way to describe who it is, what it can do, and how others can connect with it. That’s where the AgentCard comes in. This is like a digital capabilities profile published in a standard format (JSON).

It includes:

  • A unique identity and summary of the agent's purpose.
  • A contact address (endpoint) that other agents can use.
  • Accepted authentication methods like API keys or OAuth tokens.
  • Details on what the agent can handle—from push notifications to real-time updates.
  • A list of skills or functions the agent is designed to perform.

Think of it as a self-declared, standardized bio page that enables agents to automatically discover and understand each other’s roles and strengths.

Shared Goals: Tasks

A Task is the mission an agent is asked to complete. Whether it's generating a report or summarizing a document, everything is packaged into a task.

Here’s what defines a task:

  • It has a clear goal and is tracked through multiple stages like: submitted, working, waiting for input, completed, or failed.
  • Each task has a unique ID to make tracking easier.
  • Tasks store the full back-and-forth communication that happened to complete them.
  • The outcome of the task is one or more final deliverables, known as artifacts.

Tasks can also be interconnected. For example, one task's result can be used as input for another, enabling more complex workflows.

Conversations in Context: Messages

To collaborate effectively, agents need to chat—not in human language, but through structured messages. These messages are part of the task's context and tell the story of how the task is progressing.

Each message includes:

  • A role to show who sent it (e.g., the requesting agent vs. the responding one).
  • One or more content blocks (called Parts), which carry the actual message content.

Messages are like email threads inside a task, capturing every turn in the conversation.

Content Blocks: Parts

Agents don’t just send plain text. They exchange a wide variety of content types, which are broken down into modular units called Parts.

Each part is self-contained and specifies:

  • What kind of data it holds (text, JSON, image, file, etc.).
  • Metadata like filename, MIME type, or encoding if needed.

Parts allow agents to exchange everything from instructions to images, structured data, and beyond. It’s how A2A supports rich, multi-modal communication.

Final Output: Artifacts

When a task is done, the result is wrapped in an Artifact. This is the final product—the output created by the agent.

Key points about artifacts:

  • They are immutable and timestamped, providing a reliable record.
  • Each artifact can include multiple parts (just like messages).
  • Examples: A summary document, a spreadsheet, a code snippet, a generated chart.

Artifacts ensure there is a clear, unchangeable outcome from every task.

5. A2A in Action: Real-World Scenario

Let’s say you ask your digital assistant:

“Plan a business trip to Berlin, book a hotel, estimate the cost, and prepare an agenda.”

Here’s how it works:

  1. The assistant receives the request.
  2. It creates a task and breaks it into sub-tasks.
  3. It discovers agents:
  • One that books hotels.
  • One that estimates costs.
  • One that manages your calendar.

4. These agents read each other’s AgentCards and start messaging.

5. The agents work together to orchestrate solutions, seamlessly collaborating to complete each sub-task and integrate their results.

6. Each one does its part, shares results as artifacts.

7. The assistant gathers the final results and shares them with you.

Developing agents to handle such scenarios is made easier by the A2A protocol, which ensures interoperability and efficient collaboration across different platforms.

All of this happens autonomously, behind the scenes, using the A2A protocol.

It is essential to deploy agents responsibly within open standards frameworks to ensure secure, scalable, and interoperable AI systems.

6. How A2A Works Behind the Scenes: A Beginner’s Look at Its Tech Foundations

Let’s take a step back and peek under the hood of the Agent2Agent (A2A) protocol. If agents can talk, share updates, and work together so smoothly, there must be a smart system running in the background—right?

The good news is: A2A is built on technologies most web developers already know and use. So if you’re familiar with how web apps communicate, you’ll feel right at home.

For large organizations, A2A provides the foundation for secure, scalable agent collaboration. It serves as an enterprise grade ai platform, supporting robust, interoperable solutions suitable for complex systems and enterprise environments.

The Building Blocks That Power Agent Conversations

Here are the key technologies that make agent collaboration fast, secure, and reliable:

1. HTTPS: The Secure Roadway

All messages between agents travel over the internet using HTTPS, the same secure method your browser uses when visiting a bank or email site.

  • It ensures privacy so others can't eavesdrop.
  • It guarantees the message wasn't altered on the way.
  • And it’s a must-have for production environments.

2. JSON-RPC: Simple Commands in a Common Language

When one agent needs to ask another to do something—like start a task or send a message—it uses a format called JSON-RPC. Think of it as a polite, standardized way for agents to say:

“Hey, please perform this action and let me know the result.”

This format keeps things simple: requests are written in JSON (JavaScript Object Notation), which is easy for both humans and machines to read and write.

3. Server-Sent Events (SSE): Live Updates, Made Easy

For agents that need to send real-time progress updates or partial results—like streaming task output—they use Server-Sent Events (SSE).

Why SSE instead of WebSockets (another real-time tool)? Because SSE is:

  • One-way (from server to client)—which is exactly what most agent updates need.
  • Easier to implement and scale.
  • Friendly with firewalls and proxies.

SSE is perfect for keeping the client updated while keeping things simple.

A Typical Agent Conversation: Step-by-Step

Let’s now walk through what actually happens when two agents work together using A2A.

Step 1: Introduction and Discovery

Before doing anything, the client agent first learns about the other agent by visiting its public “about me” file. This is called the AgentCard and it's usually found at a well-known address (like /.well-known/agent.json).

From here, the client finds:

  • What the other agent can do.
  • How to reach it.
  • What kind of authentication is needed.
  • Whether it supports streaming, real-time updates, and more.

Step 2: Starting the Task

Once the client knows who it’s working with, it creates a task ID (a unique tag to track the job), and sends a Message to kick off the task.

There are two ways to start:

  • Regular request (message/send): Ideal for short tasks. The client sends the request and either waits or checks back later.
  • Streaming request (message/stream): Best for long tasks that produce progress updates. The connection stays open, and updates come in as they happen.

Step 3: Work in Progress

Depending on the method used, the remote agent starts processing:

  • With streaming, the client gets a steady flow of status updates, results, or thoughts from the server.
  • Without streaming, the client can keep checking in using a request like tasks/get.

This phase may involve other steps, like waiting for input or processing sub-tasks.

Step 4: Back-and-Forth (If Needed)

Sometimes, the agent may hit a point where it needs more details—maybe the request was unclear, or it needs a file or confirmation.

In that case, the task is marked as input-required, and the client can respond with another Message to fill in the missing info.

Step 5: Wrapping Up

Every task must end eventually. The final state can be:

  • Completed: Everything worked and results are ready.
  • Failed: Something went wrong.
  • Canceled: The client or server stopped the task on purpose.

Once done, the agent packages the final result as an Artifact, which the client can access or download.

Why This Setup Makes Sense

Instead of inventing new, complex tech, A2A smartly uses web standards:

  • HTTP(S): Most developers already know it.
  • JSON: Easy to read, write, and debug.
  • SSE: Real-time updates without headaches.

This makes A2A easy to adopt in existing environments, especially in large organizations that rely on secure, scalable, and well-understood systems.

By leveraging these open standards, A2A helps drive the development of an interoperable internet of agents, enabling seamless communication and automation across different platforms and vendors.

7. Who's Backing It?

The protocol is no longer just Google’s vision. Following its donation, a dedicated technology group and AI technology group have formed to support and advance the protocol. Many top companies and other enterprise leaders are investing in it:

  • Cloud giants: Google Cloud, AWS, Microsoft. Major companies have joined Google Cloud and the Linux Foundation as foundational members to support open standards and interoperability.
  • Enterprise software: Salesforce, SAP, ServiceNow, Workday, along with other enterprise leaders. This broad participation demonstrates support from the entire ecosystem of technology leaders.
  • AI ecosystem players: LangChain, Cohere.
  • Tooling and infra: MongoDB, Box.

SAP’s involvement is further underscored by Walter Sun, SVP and Global Head of AI at SAP SE, who has played a key role in SAP's participation and commitment to the A2A protocol.

Rao Surapaneni, Vice President and GM of Business Applications Platform at Google Cloud, has publicly endorsed the project, highlighting its strategic importance for agent-based AI systems.

This level of support shows the industry’s commitment to making AI agents truly interoperable.

8. What You Can Do with A2A: Practical Use Cases

A2A is already proving useful across various industries. By enabling building AI powered apps, platforms like Azure AI Foundry play a key role in designing, deploying, and managing AI agents using open protocols like A2A.

A2A allows organizations to automate and optimize business processes across different platforms and vendors. These capabilities not only improve customer experience but can also be applied to nearly any customer experience, making interactions more seamless and efficient. The protocol is designed with enterprise grade capabilities, ensuring security, scalability, and reliability for large-scale deployment of agent-based AI solutions.

E-commerce

Agents can manage:

  • Inventory tracking.
  • Price optimization.
  • Customer support responses.

Finance

Automate:

  • Report generation.
  • Budgeting tools.
  • Compliance checks.

HR & Talent

Coordinate:

  • Resume screening.
  • Scheduling interviews.
  • Generating onboarding plans.

Healthcare

Combine:

  • Patient scheduling.
  • Insurance verification.
  • Diagnosis support tools.

DevOps & IT

Unify:

  • CI/CD pipelines.
  • Monitoring bots.
  • Incident response agents.

All without building custom bridges for each integration.

9. Resources for Developers

If you’re ready to try A2A, here are your starting points:

Platform engineering plays a crucial role in building and supporting open, interoperable AI ecosystems using A2A, enabling seamless agent-to-agent interactions across diverse platforms within an open standards framework.

You can start small by writing your own AgentCard and simulating task interactions between two local agents.

10. The Bigger Picture: What the Future Holds

The A2A Protocol is more than a framework. It’s a foundation for the future of AI. Here’s why:

  • It enables agent ecosystems, not isolated tools, by supporting agentic AI, autonomous agents, and intelligent agents that can seamlessly interact and collaborate.
  • It encourages open collaboration, not closed platforms, serving as both a unified AI platform and an open platform for agent-to-agent (A2A) communication.
  • It aligns with the move toward decentralized, task-driven AI systems, providing the broadest and deepest set of tools for agent interoperability.

The future of enterprise AI lies in open standards and protocols like A2A, which are a critical step in combining open interoperability to orchestrate solutions across diverse platforms and vendors. This approach enables life alongside Google Cloud and other major platforms, fostering scalable, secure, and community-driven agent collaboration.

Think of A2A as the protocol that might someday let your AI assistant hire a freelancer, pay an invoice, and update your website—all by collaborating with other agents across the internet.

We are entering the era of The Internet of Agents.

Final Thoughts

The Agent2Agent Protocol is one of those technologies that doesn’t make a lot of noise but quietly powers big change.

With A2A, we move from “smart tools” to “smart teams” of agents. This isn’t just more automation—it’s smarter automation.

The protocol’s open development model, supported by the Linux Foundation, addresses intellectual property concerns by promoting transparent management and open standards, which encourages broad community participation.

Whether you’re a developer, product manager, or tech enthusiast, this is a moment to pay attention.