How Google’s A2A Protocol Enables Seamless AI Agent Collaboration

Google introduced an open protocol called A2A (Agent‑to‑Agent) that lets AI agents built on different platforms and by different vendors communicate, collaborate and jointly complete tasks.

It acts as a universal language for agents, enabling the formation of an intelligent collaborative network.

“Allow AI agents from different companies to cooperate, converse and divide tasks like humans.”

🧠 A universal “language” for AI agents

🌐 Like HTTP for web pages, A2A is the communication protocol for agents

👷‍♂️ Designed specifically for multi‑agent cooperation

Background: Current AI agents are isolated “silos” that cannot easily share work, use different platforms, architectures and formats, making cross‑agent collaboration impossible.

A2A solves this by allowing agents to plug together like LEGO blocks and lets enterprises build “AI teams” that handle tasks.

Core goals:

Break the information silos between agents

Support cross‑vendor and cross‑cloud collaboration

Reduce integration complexity and long‑term maintenance costs

A2A vs. MCP

A2A is a conversation between agents, while MCP is an agent calling tools from a toolbox.

Design principles (5 core ideas)

Multimodal and asynchronous capabilities

Multimodal communication (text, image, audio, video)

Multi‑language / natural‑language task collaboration (adapts LLM output)

Asynchronous long‑running tasks can be paused and resumed (e.g., video rendering, data training)

How A2A works

The protocol is built on a core structure illustrated below.

Workflow example

<code>你：我想找一个会生成 PPT 的 AI Agent

↓（Agent Card 发现）

Agent A：我找到了 Agent B，它专门做 PPT

↓（发任务）

Agent A → Agent B：请根据这份内容生成一个 10 页的商业计划书

↓（执行任务）

Agent B：已完成，请看这里：[artifact_url]

↓（你下载文件 or 发给下一个 Agent）</code>

Agent Card (capability description)

It tells other agents what it can do, which interfaces it supports and which data formats it accepts – essentially an API self‑description.

Example Agent Card JSON

<code>{
  "id": "agent://vendor/example-agent",
  "name": "Resume Analyzer Agent",
  "capabilities": ["parse_resume", "rank_candidates"],
  "input_format": "application/json",
  "output_format": "application/json+artifact",
  "authentication": {
    "type": "OAuth2",
    "scopes": ["task.read", "task.write"]
  }
}</code>

Task object

Every task is a to‑do item containing an ID, the originating agent, the receiving agent, status (pending, running, success, failure) and the output artifact.

Task ID

Initiating agent

Receiving agent

Status

Result artifact (text, image, PPT, JSON, DB query, etc.)

Long‑running tasks such as video analysis or document approval are also supported.

Message Part

Agents can send rich content—not just plain text—allowing responses to be embedded directly into front‑end UIs for smarter, more usable interactions.

Use cases

Multiple agents work together like a pipeline to complete complex tasks, e.g., a recruitment workflow where a manager triggers a search, a candidate‑matching agent, an interview‑scheduling agent and a background‑check agent collaborate under A2A.

Value: No need to develop multiple APIs; following A2A lets all agents cooperate naturally, reducing development burden.

Adoption

More than 50 technology companies and consulting firms support A2A, including Google Cloud, LangChain, MongoDB, Salesforce, SAP, ServiceNow, Intuit, PayPal, JetBrains, and consulting partners such as Accenture, BCG, Deloitte, McKinsey, Infosys, Wipro, TCS, KPMG.

Application directions

Customer‑experience automation (AskAI, Box)

Enterprise automation and workflow orchestration (SAP, Salesforce, Workday)

AI‑agent development toolchains (Weights & Biases, LangChain, JetBrains)

Security mechanisms

OAuth2 – standard authorization protocol

API Token – simplified integration

Mutual TLS – encrypted connections

Every communication between agents requires permission verification to prevent abuse.

For more details, see the full specification draft and code examples on the GitHub repository.

GitHub: https://github.com/google/A2A

Official announcement: https://developers.googleblog.com/en/a2a-a-new-era-of-agent-interoperability/