With joint support from more than 50 companies, Google's A2A protocol leads the way in establishing a new standard for AI agent interoperability

Recently (2025-04-10), Google released something called A2A (Agent to Agent Protocol). It sounds very high-end, but in fact it solves a very down-to-earth problem: how to make different AI Agents collaborate with each other .

A2A open source protocol address: https://github.com/google/A2A

Why do Agents need to "chat" with each other?

Imagine this scenario: You use the smart assistant on your phone to make an appointment with a doctor, but the hospital has its own AI agent system. Before A2A, the two agents could not communicate directly, just like one only speaks Chinese and the other only speaks English, with no translation in between. The result? You have to pass messages back and forth and manually copy and paste information. Isn't it annoying?

The A2A protocol is designed to solve this problem - it is equivalent to establishing a "Mandarin" standard for the AI ​​world, allowing all Agents, regardless of their origin, to communicate in the same "language".

What exactly is A2A? In simple terms

The A2A protocol is a set of rules that tell agents: "When you communicate with each other, please send messages like this, respond like that, and transmit data in this format..."

Let’s take an example from real life:

Xiao Ming (user) asks his shopping assistant (AI-1): "Please buy me a pair of sneakers." In the past, this assistant might recommend a few to you, and then you can place the order yourself. But with A2A, it can directly:

• Inventory system AI confirms which shoes are in stock
• Payment system AI helps you complete payment
• AI in logistics system arranges shipment tracking

You only need to click “confirm” at the end of the whole process, without having to switch back and forth between multiple systems.

What real problems does A2A solve?

1. Breaking down information silos

Nowadays, many companies use various systems internally: sales use sales systems, documents are stored in WPS, HR uses DingTalk or Feishu... In the past, these systems were independent of each other and data was not interoperable. With A2A, agents in each system can communicate directly and information can flow automatically.

2. Improved work efficiency

Work that previously required manual copying and pasting between multiple systems can now be done by agents themselves. For example, to prepare a sales proposal, you may need to obtain information from multiple sources, such as the product database, customer database, and pricing system. With A2A, this can be done with just one command.

3. Make professional AI more professional

Just as human society requires division of labor and cooperation (doctors treat patients, chefs cook), so do agents. With A2A, each agent can focus on doing well in his or her own area of ​​expertise, and when other capabilities are needed, they can directly "find colleagues" to cooperate.

A2A and MCP: Complementarity rather than competition

Many people may ask: What is the difference between A2A and the MCP (Model Context Protocol) previously launched by Anthropic? This is a good question.

• MCP (Model Context Protocol) : focuses on how AI models interact with external tools and data sources, providing AI with the ability to retrieve and use external information.
• A2A (Agent to Agent Protocol) : focuses on communication and collaboration between different agents, allowing them to share tasks, exchange information and coordinate actions.

They are not in competition, but complementary .

Image source: The Beginning of the End of Explicit Programming

You can  think of MCP as the interface between AI and the toolbox , and  A2A as the way Agent communicates with other Agents .

Let me give you a simple analogy:

• MCP  - You know, someone provides a hammer and you borrow or rent it, and you have to do the work yourself .
• A2A  - You know someone who is good with a hammer, so you just hire him to do the job for you .

Both scenarios require communication, the former using the MCP protocol and the latter using the A2A protocol .

Let’s talk briefly about how it works

Without going into technical details, just imagine how human society works:

1. Competence Business Card : Each Agent has his or her own "Competence Business Card" which explains "what I can do"
2. Task allocation : After your main agent sees the task, it decides which parts to do itself and which parts need to be "outsourced"
3. Collaborative communication : Different agents transmit information to each other and coordinate work
4. Progress feedback : Throughout the process, you will be continuously updated with progress and results

Just like when you assign a task to a secretary, she may coordinate multiple departments of the company to complete it, but you only need to communicate with the secretary.

What are the benefits for ordinary people?

1. Save time and effort : You can complete complex tasks that used to require switching between multiple applications in one sentence
2. Smarter services : For example, smart home devices can automatically coordinate with each other (air conditioning and fresh air systems can automatically coordinate and adjust)
3. Personalized experience : Your personal agent assistant can negotiate with agents of various services to customize the experience according to your preferences

Why is this so important?

After Google released A2A, more than 50 large companies immediately expressed their support, including enterprise software giants such as Salesforce and SAP. The fact that so many big companies have stood up for it shows that this matter is really critical.

Its significance is a bit like the formulation of the Internet protocol. Without standard protocols, the network equipment of each company cannot be interconnected; similarly, without A2A, each company's AI can only work independently and cannot form a true AI ecosystem.

Impact on the future

As A2A becomes more popular, we may see:

• Agent service market : Agents in professional fields can be called like services (legal advisory agents, medical diagnosis agents, etc.)
• Seamless experience : consistent Agent experience across platforms and devices
• New career opportunities : New jobs for designing and managing Agent teams

To sum up

The A2A protocol may seem like just a technical standard, but in fact it is changing the fundamental way AI works -  from working alone to working in a team .

Just as human society has formed a complex civilization because of language communication, the world of artificial intelligence (AI) has begun to build a more complex and powerful collaborative network because of "universal languages" such as A2A.

I personally believe that the future of AI is not a super-intelligent entity, but an ecosystem where countless professional AIs collaborate with each other . A2A is the "Mandarin" in this ecosystem.