A2A Protocol

Integrating A2A Protocol - Intelligent Agent Communication Solution for BeeAI Framework

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Integrating A2A Protocol - Intelligent Agent Communication Solution for BeeAI Framework

🎯 Key Points (TL;DR)

  • A2A Protocol: Linux Foundation-supported open standard for AI agent communication, enabling cross-platform agent collaboration
  • BeeAI Integration: Seamlessly integrate external agents and expose internal agents through A2AAgent and A2AServer
  • ACP Migration: IBM's ACP protocol has been merged into A2A, providing complete migration guides and tools
  • Enterprise Applications: Supports multi-vendor ecosystems including Google, Microsoft, AWS, Cisco, and more

Table of Contents

  1. What is A2A Protocol?
  2. A2A Integration in BeeAI Framework
  3. Migration Guide from ACP to A2A
  4. Implementation Steps and Best Practices
  5. Frequently Asked Questions

What is A2A Protocol?

Agent2Agent (A2A) Protocol is an open standard for AI agent communication developed by the Linux Foundation. This protocol aims to solve interoperability challenges in current AI agent ecosystems, enabling seamless collaboration between agents from different platforms, frameworks, and ecosystems.

Core Features of A2A Protocol

  • Cross-platform Compatibility: Supports communication between agents built with different technology stacks
  • Standardized Interface: Provides unified message formats and communication protocols
  • Enterprise-grade Support: Backed by major tech companies including Google, Microsoft, AWS, IBM
  • Open Source Ecosystem: Based on open standards, promoting community innovation and collaboration

💡 Industry Background

The birth of A2A protocol stems from the urgent need for unified AI agent communication standards. As AI agent applications grow rapidly, interoperability between different vendors and frameworks has become a key challenge.

A2A Integration in BeeAI Framework

BeeAI framework implements A2A protocol integration through two core components:

A2A Agent (Client)

A2AAgent allows you to easily connect to external agents using the A2A protocol.

# Install dependencies
pip install beeai-framework
pip install 'beeai-framework[a2a]'

Key Features:

  • Connect to external A2A-compatible agents
  • Handle cross-platform message passing
  • Support multiple input/output modes

A2A Server (Server)

A2AServer enables you to expose agents built in the BeeAI framework through the A2A protocol.

Core Advantages:

  • Convert existing BeeAI agents to A2A-compatible services
  • Support standardized agent discovery and interaction
  • Provide rich metadata and capability descriptions

Migration Guide from ACP to A2A

Migration Background

IBM Research's Agent Communication Protocol (ACP) launched in March 2025 has been officially merged into the A2A protocol. This merger aims to:

  • Avoid standard fragmentation
  • Accelerate protocol development
  • Integrate technical advantages
  • Establish a unified ecosystem

Quick Migration Checklist

✅ Update Dependencies: acp_sdk → beeai_sdk
✅ Update Imports: Modify import statements and function signatures
✅ Replace Metadata: Metadata → AgentDetail
✅ Update Message Processing: Adopt new message processing methods
✅ Update Trajectory and References: Use new extension system
✅ Use LLM Service Extensions: Integrate platform-managed LLM configurations

Key Code Changes Comparison

Component ACP (Old) A2A (New)
Dependencies acp-sdk>=1.0.0 beeai-sdk>=0.3.0
Message Processing input[-1].parts[0].content message.parts loop processing
Context Context RunContext
Response Output MessagePart(content=text) AgentMessage(text=text)
LLM Configuration Environment variables LLMServiceExtensionServer

Detailed Migration Steps

1. Update Dependencies and Imports

Old (ACP):

from acp_sdk import Message, Metadata, Link
from acp_sdk.server import Context, Server

New (A2A):

from a2a.types import AgentSkill, Message
from beeai_sdk.server import Server
from beeai_sdk.server.context import RunContext
from beeai_sdk.a2a.extensions import AgentDetail

2. Update Agent Decorators

Old (ACP):

@server.agent(
    name="chat_agent",
    description="Chat Assistant",
    metadata=Metadata(...)
)
async def agent_function(input: list[Message], context: Context):

New (A2A):

@server.agent(
    name="Chat Agent",
    default_input_modes=["text", "application/pdf"],
    default_output_modes=["text"],
    detail=AgentDetail(
        interaction_mode="multi-turn",
        user_greeting="Hello! I'm your AI assistant.",
        version="1.0.0"
    )
)
async def agent_function(
    message: Message,
    context: RunContext,
    trajectory: Annotated[TrajectoryExtensionServer, TrajectoryExtensionSpec()],
):

Implementation Steps and Best Practices

Environment Setup

# 1. Install BeeAI Framework
pip install beeai-framework

# 2. Install A2A Extension
pip install 'beeai-framework[a2a]'

# 3. Verify Installation
python -c "import beeai_sdk; print('Installation successful')"

Creating A2A Compatible Agents

from beeai_sdk.server import Server
from beeai_sdk.a2a.extensions import AgentDetail, AgentDetailTool
from a2a.types import AgentSkill, Message

server = Server()

@server.agent(
    name="Smart Assistant",
    default_input_modes=["text", "text/plain"],
    default_output_modes=["text"],
    detail=AgentDetail(
        interaction_mode="multi-turn",
        user_greeting="Hello! I can help you answer questions.",
        version="1.0.0",
        tools=[
            AgentDetailTool(
                name="Search",
                description="Search for latest information"
            )
        ]
    ),
    skills=[
        AgentSkill(
            id="chat",
            name="Conversation",
            description="Intelligent conversation assistant",
            tags=["chat", "Q&A"]
        )
    ]
)
async def chat_agent(message: Message, context: RunContext):
    # Process user message
    user_text = ""
    for part in message.parts:
        if part.root.kind == "text":
            user_text = part.root.text
    
    # Generate response
    response = f"You said: {user_text}"
    yield response

✅ Best Practices

  • Use descriptive agent names and detailed descriptions
  • Properly configure input/output modes
  • Provide clear user greetings
  • Describe agent capabilities and tools in detail

Integrating External A2A Agents

from beeai_sdk.a2a.client import A2AAgent

# Connect to external agent
external_agent = A2AAgent(
    endpoint="https://api.example.com/a2a",
    agent_id="external_chat_agent"
)

# Send message
async def interact_with_external():
    response = await external_agent.send_message("Hello, external agent!")
    return response

🤔 Frequently Asked Questions

Q: What's the difference between A2A protocol and other AI agent communication standards?

A: A2A protocol has the following unique advantages:

  • Linux Foundation Support: Ensures long-term maintenance and neutrality
  • Multi-vendor Support: Joint participation from Google, Microsoft, IBM, etc.
  • High Standardization: Provides complete specifications and implementation guides
  • Rich Ecosystem: Supports multiple programming languages and frameworks

Q: Which programming languages does A2A protocol support?

A: Currently A2A protocol supports:

  • Python: Full support, including BeeAI SDK
  • JavaScript/TypeScript: Through official SDK
  • Java: Community-contributed implementations
  • Go: Experimental support

Q: How to handle secure communication between A2A agents?

A: A2A protocol provides multi-layer security guarantees:

  • Transport Encryption: Supports TLS/SSL
  • Authentication: API keys and OAuth 2.0
  • Access Control: Role-based permission management
  • Audit Logs: Complete communication records

Q: Does BeeAI framework support local deployment?

A: Yes, BeeAI framework fully supports local deployment:

  • Containerized Deployment: Provides Docker images
  • Cloud Native Support: Kubernetes configuration files
  • Hybrid Deployment: Supports local and cloud hybrid architecture
  • Offline Operation: Can run without internet connection

Summary and Action Recommendations

A2A protocol represents an important milestone in AI agent communication standardization. Through BeeAI framework integration, developers can:

Immediate Action Steps

  1. Evaluate Existing Systems: Check current agent architecture and communication needs
  2. Install BeeAI SDK: Use pip install 'beeai-framework[a2a]'
  3. Create Test Agents: Follow this guide to create your first A2A compatible agent
  4. Plan Migration Path: If using ACP, develop detailed migration plans
  5. Join Community: Participate in A2A project GitHub discussions and contributions

Long-term Strategic Recommendations

  • Standardization First: Make A2A protocol the preferred standard for agent communication
  • Ecosystem Building: Actively participate in A2A community, contribute tools and best practices
  • Skill Enhancement: Train teams to master A2A protocol and BeeAI framework
  • Monitor Development: Follow protocol updates and new feature releases

⚠️ Important Reminder

A2A protocol is still rapidly evolving. It's recommended to regularly check official documentation and update logs to ensure using the latest version and best practices.

Related Resources:

📚 Protocol Specifications & Guides

🔧 SDKs & Development Tools

💻 Programming Language Implementations

🤖 Practical Application Examples

🔌 Extensions

🛠️ Debugging & Tools

🔗 Framework Integration

⚖️ Protocol Comparison Analysis

🤝 Protocol Integration

🏢 Industry Analysis & Trends

📖 Resource Directory

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