🔄 Google Agent-to-Agent (A2A) Communication SDK – In-Depth Guide with Python Example

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🚀 Overview

Google's Agent-to-Agent (A2A) SDK is a powerful communication layer enabling multiple conversational agents (LLMs, rule-based bots, or services) to collaborate seamlessly within a shared context. It facilitates:

Multi-agent orchestration
Shared memory and context
Agent coordination via events
Plug-and-play interoperability across modalities

Used internally at Google (e.g., Gemini, Bard integrations), the A2A SDK is now open-source and aims to become the backbone of multi-agent conversational systems.

🧠 Key Concepts

Agent
An autonomous unit capable of receiving input, taking action, and producing output.
Exchange
A communication channel that routes messages and events between agents.
Session
A persistent interaction space where multiple agents operate and share state.
Events
Messages or signals that trigger agent actions (e.g., TextInputEvent, AgentResponseEvent, ToolUseEvent).

🧱 Architecture Diagram

Example

Checkout the end-to-end implementation of A2A client and server here at repo.

🤖 Building More Advanced Agents

A2A supports event-driven composition. You can register agents that:

Call tools or external APIs
Chain multiple agents (like planners and executors)
Share session state
Handle multi-turn conversations

🌐 Use Case Examples

Use Case	Description
Conversational RAG	Planner agent routes questions, retriever agent fetches from vector DB.
Voicebot + LLM	Voice agent transcribes speech, LLM responds, TTS agent speaks back.
Customer Support	One agent fetches customer info, another handles FAQs, another resolves.
Copilot Tooling	Planner agent routes requests to different developer tools or copilots.

📌 Summary

Component	Role
Agent	Receives events, produces responses
Exchange	Event router and session manager
Event	Input/output signal used for agent communication
Session	Shared memory space across agents in a flow