Overview of Google A2A Protocol

The Agent2Agent Protocol (A2A) is an open standard developed by Google that enables seamless communication and collaboration between AI agents across different platforms and frameworks. A2A addresses the fragmentation in the AI agent ecosystem by providing a unified way for agents to discover capabilities, delegate tasks, and share results.

What is the full form of A2A?

A2A stands for Agent2Agent or Agent-to-Agent Protocol, defining how AI agents communicate with each other securely and efficiently.

A2A Protocol Overview

A2A Protocol Architecture Overview

Core Capabilities

Capability Discovery

Agents expose their capabilities through standardized Agent Cards (JSON metadata), allowing other agents to discover and utilize their services.

Task Management

Structured task lifecycle with support for synchronous, asynchronous, and streaming interactions between agents.

Multimodal Communication

Support for diverse data types including text, image, audio, and video, enabling rich interactions between agents.

Security & Privacy

Enterprise-grade authentication and authorization mechanisms to ensure secure agent interactions and data privacy.

Relationship with MCP

The Agent2Agent Protocol (A2A) complements Anthropic's Model Context Protocol (MCP), with A2A focusing on communication between AI agents, while MCP specializes in agent-to-tool connections.

A2A vs MCP Comparison

Comparison between A2A and MCP protocols

Protocol Specification

The A2A protocol is built on standard web technologies to ensure broad compatibility and easy integration with existing systems. This section covers the technical specifications of the protocol architecture, agent discovery mechanism, task management, and security features.

2.1 Architecture

A2A is implemented as a JSON-RPC 2.0 over HTTP(S) protocol, allowing for synchronous, streaming, and asynchronous communication patterns between agents. This architecture provides flexibility while leveraging established web standards.

A2A Protocol Workflow

A2A Protocol communication workflow

  • Transport Layer: HTTPS for secure communication
  • Message Format: JSON-RPC 2.0 for structured request-response patterns
  • Communication Patterns:
    • Synchronous: Standard HTTP request-response
    • Streaming: Server-Sent Events (SSE) for real-time updates
    • Asynchronous: Polling with task IDs for long-running operations
  • Content Types: Support for text, JSON, binary data, and multipart content

2.2 Agent Discovery

A2A uses Agent Cards for capability discovery, allowing agents to expose their functionality in a standardized format. An Agent Card is a JSON document typically located at /.well-known/agent.json that describes an agent's capabilities and endpoints.

Agent Card Example:

{
  "name": "Currency Converter Agent",
  "description": "Converts between currencies using real-time exchange rates",
  "version": "1.0.0",
  "contact": "support@example.com",
  "endpoints": {
    "tasks": "https://api.example.com/a2a/tasks",
    "stream": "https://api.example.com/a2a/stream"
  },
  "auth": {
    "type": "api_key",
    "in": "header",
    "name": "X-API-Key"
  },
  "capabilities": [
    {
      "id": "convert_currency",
      "name": "Convert Currency",
      "description": "Converts an amount from one currency to another",
      "parameters": {
        "type": "object",
        "properties": {
          "amount": {
            "type": "number",
            "description": "The amount to convert"
          },
          "from": {
            "type": "string",
            "description": "Source currency code (ISO 4217)"
          },
          "to": {
            "type": "string",
            "description": "Target currency code (ISO 4217)"
          }
        },
        "required": ["amount", "from", "to"]
      },
      "returns": {
        "type": "object",
        "properties": {
          "converted_amount": {
            "type": "number"
          },
          "rate": {
            "type": "number"
          },
          "timestamp": {
            "type": "string",
            "format": "date-time"
          }
        }
      }
    }
  ]
}

2.3 Task Management

A2A provides a standardized task lifecycle management system that tracks tasks through various states from creation to completion, supporting both simple and complex multi-step operations.

A2A Task Management Workflow

Task lifecycle in the A2A protocol

Task states in the A2A protocol include:

  • Created: Task has been submitted but not yet started
  • Working: Agent is actively processing the task
  • NeedsInput: Additional information is required from the requester
  • Completed: Task has been successfully completed
  • Failed: Task encountered an error and could not be completed
  • Canceled: Task was canceled by the requester or agent

Tasks are uniquely identified by IDs, allowing for tracking and management across multiple interactions.

2.4 Security

A2A implements enterprise-grade security features to protect agent communications and sensitive data, aligning with industry standards for authentication and authorization.

Authentication Methods

  • API Keys
  • OAuth 2.0
  • JWT (JSON Web Tokens)
  • Client Certificates

Security Features

  • HTTPS encryption
  • Input validation
  • Rate limiting
  • Audit logging
  • Privacy controls

A2A's security model is designed to protect not only the communication between agents but also the internal state and intellectual property of each agent, ensuring that agents can collaborate without exposing sensitive information.

Implementation Guides

This section provides practical guidance for implementing A2A in your applications, with step-by-step tutorials for both Python and JavaScript environments, as well as integration instructions for popular AI frameworks.

3.1 Quick Start

Follow these steps to get started with A2A implementation:

  1. Set up development environment

    Install the A2A SDK for your preferred language:

    # Python
    pip install google-a2a
    
    # JavaScript
    npm install @google/a2a-sdk
  2. Create an Agent Card

    Define your agent's capabilities in a JSON file following the A2A specification.

  3. Implement API endpoints

    Create the necessary endpoints for task submission, status checking, and streaming.

  4. Test integration

    Use the A2A test suite to verify your implementation.

3.2 Python Implementation

This tutorial demonstrates how to implement a simple currency conversion agent using Python and the A2A SDK:

from google_a2a import A2AServer, AgentCard, Task, TaskStatus
from fastapi import FastAPI, HTTPException
import uvicorn
import requests

app = FastAPI()
a2a_server = A2AServer(app)

# Define agent card
agent_card = AgentCard(
    name="Currency Converter",
    description="Converts between currencies using real-time exchange rates",
    version="1.0.0",
    capabilities=[
        {
            "id": "convert_currency",
            "name": "Convert Currency",
            "description": "Converts an amount from one currency to another",
            "parameters": {
                "type": "object",
                "properties": {
                    "amount": {"type": "number"},
                    "from": {"type": "string"},
                    "to": {"type": "string"}
                },
                "required": ["amount", "from", "to"]
            }
        }
    ]
)

# Register agent card
a2a_server.register_agent_card(agent_card)

# Implement task handler
@a2a_server.task_handler("convert_currency")
async def convert_currency(task: Task):
    params = task.parameters
    amount = params.get("amount")
    from_currency = params.get("from")
    to_currency = params.get("to")

    # Update task status to working
    await task.update_status(TaskStatus.WORKING)

    try:
        # Call external API for exchange rates (for example)
        response = requests.get(
            f"https://api.exchangerate-api.com/v4/latest/{from_currency}"
        )
        data = response.json()
        rate = data["rates"].get(to_currency)

        if not rate:
            raise ValueError(f"Exchange rate not found for {to_currency}")

        converted_amount = amount * rate

        # Complete task with result
        await task.complete({
            "converted_amount": converted_amount,
            "rate": rate,
            "timestamp": data["time_last_updated"]
        })

    except Exception as e:
        # Handle errors
        await task.fail(str(e))

if __name__ == "__main__":
    uvicorn.run("app:app", host="0.0.0.0", port=8000)

3.3 JavaScript Implementation

Here's how to implement the same currency conversion agent using Node.js and Express:

const express = require('express');
const { A2AServer, TaskStatus } = require('@google/a2a-sdk');
const axios = require('axios');

const app = express();
const port = 8000;

// Initialize A2A server
const a2aServer = new A2AServer({
  name: "Currency Converter",
  description: "Converts between currencies using real-time exchange rates",
  version: "1.0.0",
  capabilities: [
    {
      id: "convert_currency",
      name: "Convert Currency",
      description: "Converts an amount from one currency to another",
      parameters: {
        type: "object",
        properties: {
          amount: { type: "number" },
          from: { type: "string" },
          to: { type: "string" }
        },
        required: ["amount", "from", "to"]
      }
    }
  ]
});

// Register the A2A server with Express
a2aServer.registerExpress(app);

// Implement task handler
a2aServer.registerTaskHandler("convert_currency", async (task) => {
  const { amount, from, to } = task.parameters;

  // Update task status to working
  await task.updateStatus(TaskStatus.WORKING);

  try {
    // Call external API for exchange rates
    const response = await axios.get(
      \`https://api.exchangerate-api.com/v4/latest/\${from}\`
    );
    const data = response.data;
    const rate = data.rates[to];

    if (!rate) {
      throw new Error(\`Exchange rate not found for \${to}\`);
    }

    const convertedAmount = amount * rate;

    // Complete task with result
    await task.complete({
      converted_amount: convertedAmount,
      rate: rate,
      timestamp: data.time_last_updated
    });
  } catch (error) {
    // Handle errors
    await task.fail(error.message);
  }
});

// Start the server
app.listen(port, () => {
  console.log(\`Currency Converter agent listening on port \${port}\`);
});

3.4 Framework Integration

A2A can be integrated with popular AI agent frameworks to enhance their capabilities with cross-agent communication:

Framework Integration Method Features
LangGraph Native A2A support via langgraph.a2a module Graph-based agent workflows with A2A communication
CrewAI A2A adapter available (crewai-a2a) Multi-agent crews with specialized roles
Google ADK Built-in A2A support Integration with Google AI/ML services
Semantic Kernel Plugin: Microsoft.SemanticKernel.A2A Connect Microsoft's agent framework with A2A

API Reference

This section provides detailed information about the A2A API endpoints, request/response formats, and error handling.

4.1 Core Methods

A2A defines the following core methods for agent communication:

tasks/send

Purpose: Submit a synchronous task to an agent and wait for completion

HTTP Method: POST

Parameters:

  • capability_id: ID of the capability to invoke
  • parameters: Task-specific parameters as defined in the Agent Card
  • timeout (optional): Maximum wait time in seconds

Returns: Task result or error

tasks/sendAsync

Purpose: Submit an asynchronous task and get a task ID for later polling

HTTP Method: POST

Parameters:

  • capability_id: ID of the capability to invoke
  • parameters: Task-specific parameters
  • callback_url (optional): URL to receive completion notification

Returns: Task ID and initial status

tasks/sendSubscribe

Purpose: Submit a task and receive streaming updates via Server-Sent Events

HTTP Method: POST

Parameters:

  • capability_id: ID of the capability to invoke
  • parameters: Task-specific parameters

Returns: SSE stream with task updates and final result

tasks/{task_id}/status

Purpose: Check the status of an asynchronous task

HTTP Method: GET

Parameters:

  • task_id: ID of the task to check

Returns: Current task status and result if completed

tasks/{task_id}/cancel

Purpose: Cancel an in-progress task

HTTP Method: POST

Parameters:

  • task_id: ID of the task to cancel
  • reason (optional): Explanation for cancellation

Returns: Confirmation of cancellation

4.2 Request/Response Formats

All A2A requests and responses follow JSON-RPC 2.0 format:

Request Format

{
  "jsonrpc": "2.0",
  "method": "tasks/send",
  "params": {
    "capability_id": "convert_currency",
    "parameters": {
      "amount": 100,
      "from": "USD",
      "to": "EUR"
    }
  },
  "id": "req-123"
}

Response Format

{
  "jsonrpc": "2.0",
  "result": {
    "converted_amount": 92.45,
    "rate": 0.9245,
    "timestamp": "2025-05-14T10:15:30Z"
  },
  "id": "req-123"
}

4.3 Error Handling

A2A defines standard error codes and response formats for error conditions:

Error Response Format

{
  "jsonrpc": "2.0",
  "error": {
    "code": -32602,
    "message": "Invalid parameters",
    "data": {
      "details": "Currency code 'XYZ' is not valid"
    }
  },
  "id": "req-123"
}
Error Code Message Description
-32600 Invalid Request Request is not valid JSON-RPC 2.0
-32601 Method not found Requested method is not supported
-32602 Invalid parameters Parameters do not match schema definition
-32603 Internal error Internal server error during processing
-32000 Task not found The specified task ID does not exist
-32001 Task timeout Task execution exceeded the timeout period
-32002 Authentication failed Invalid or missing authentication credentials

Use Cases & Examples

A2A enables a wide range of practical applications across various industries. This section showcases real-world examples of how A2A can be implemented to solve business challenges.

Recruitment automation with A2A

Recruitment Automation

Multiple specialized agents collaborate to screen candidates, schedule interviews, and analyze responses.

HR Scheduling Analysis
View case study →
Automotive maintenance with A2A

Automotive Maintenance

Connected agents manage diagnostic data, parts inventory, and technician scheduling for efficient repairs.

Automotive Logistics IoT
View case study →
Supply chain optimization with A2A

Supply Chain Optimization

Agents coordinate inventory, logistics, and demand forecasting across global supply networks.

Logistics Forecasting Enterprise
View case study →

Featured Example: Multi-Agent Collaboration

Multi-Agent Collaboration with A2A

Multi-agent workflow for customer service use case

Implementation Steps

  1. Deploy specialized agents for different aspects of customer service
  2. Configure Agent Cards to expose each agent's capabilities
  3. Implement a coordinator agent that directs customer queries to appropriate specialists
  4. Use A2A for secure communication between coordinator and specialists
  5. Aggregate responses and maintain context across the conversation

This approach allows organizations to create specialized agents for different domains while maintaining a seamless customer experience through A2A-enabled collaboration.

Community & Resources

Join the growing A2A community to get support, share your implementations, and contribute to the protocol's development.

Community Channels

How to Contribute

  • Report issues and suggest improvements on GitHub
  • Submit pull requests for bug fixes and features
  • Share your A2A implementations and use cases
  • Provide feedback through the A2A feedback form

Partner Ecosystem

Join over 50+ partners contributing to the A2A ecosystem:

Salesforce
Atlassian
Box
Microsoft
SAP
Accenture

Learning Resources

Official Documentation

Complete technical documentation and guides for the A2A protocol.

View documentation →

Sample Projects

Repository of working examples and starter templates for A2A integration.

Explore samples →

Tutorial Videos

Step-by-step video guides for implementing A2A in your applications.

Watch tutorials →

Submit Feedback

Help improve A2A by sharing your experiences, challenges, and suggestions with the development team.

Submit Feedback

Future Developments

A2A is continuously evolving to address emerging needs and enhance agent interoperability. Here's what's on the horizon for upcoming releases.

Development Roadmap

Q3 2025: Production-Ready Release

  • Stable API with backward compatibility guarantees
  • Production-grade security and performance optimizations
  • Comprehensive documentation and case studies

Q4 2025: Enhanced Authorization

  • Formalized authorization schemes
  • Fine-grained permission controls
  • Integration with enterprise identity providers

Q1 2026: Dynamic Agent Capabilities

  • Implementation of QuerySkill() for discovering unsupported capabilities
  • Dynamic UX negotiation for richer interactions
  • Enhanced multimodal support for AR/VR applications

Planned Enhancements

Technical Improvements

  • Streaming reliability enhancements
  • Improved error handling and recovery
  • Performance optimizations for large payloads
  • Extended multimodal content support
  • Advanced authentication mechanisms

Ecosystem Enhancements

  • Agent directory and discovery service
  • Certification program for A2A implementations
  • More SDK language support (Go, Java, Ruby)
  • Integration with popular LLM frameworks
  • Expanded partner ecosystem

Participate in Development

A2A is an open standard, and community contributions are welcome. You can influence its future by:

  • Following and contributing to discussions on GitHub Discussions
  • Submitting feature requests and bug reports through GitHub Issues
  • Participating in community calls and events (announced on the repository)
  • Testing pre-release versions and providing feedback

Stay Updated

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Need additional help?

If you have questions or need personalized assistance with A2A implementation, reach out to our support team or community.