Skip to content

a2a-protocol-tutorial

Directory actions

More options

Directory actions

More options

Latest commit

 

History

History

a2a-protocol-tutorial

README.md

layout default
title A2A Protocol Tutorial
nav_order 195
has_children true
format_version v2

A2A Protocol Tutorial: Building Interoperable Agent Systems With Google's Agent-to-Agent Standard

Learn how agents discover, communicate, and delegate tasks to each other using the A2A protocol — the open standard (now Linux Foundation) for agent-to-agent interoperability.

GitHub Repo License Stars

Why This Track Matters

The AI ecosystem is converging on two complementary standards: MCP (Model Context Protocol) for connecting agents to tools and data, and A2A (Agent-to-Agent) for connecting agents to each other. Together they form the complete agent interoperability stack.

A2A solves a critical gap: how do independently built agents — potentially from different vendors, frameworks, and platforms — discover each other's capabilities and collaborate on tasks? Without A2A, every multi-agent system invents its own bespoke integration layer.

This track focuses on:

  • understanding the A2A protocol specification and its design principles
  • building agents that publish discoverable Agent Cards
  • implementing task lifecycle management with streaming updates
  • securing agent-to-agent communication with OAuth2 and identity verification
  • combining A2A with MCP to create the full agent ecosystem architecture

Current Snapshot (auto-updated)

Mental Model

flowchart LR
    subgraph MCP ["MCP (Agent → Tool)"]
        A1[AI Agent] -->|calls| T1[Tool Server]
        A1 -->|reads| R1[Resource / Data]
    end

    subgraph A2A ["A2A (Agent → Agent)"]
        A2[Client Agent] -->|discovers| AC[Agent Card]
        A2 -->|sends task| A3[Remote Agent]
        A3 -->|streams updates| A2
        A3 -->|returns artifact| A2
    end

    User[User / Host App] --> A1
    User --> A2
    A3 -->|uses tools via MCP| T2[MCP Server]

    classDef mcp fill:#e1f5fe,stroke:#01579b
    classDef a2a fill:#fff3e0,stroke:#ef6c00
    classDef user fill:#e8f5e8,stroke:#1b5e20

    class A1,T1,R1 mcp
    class A2,AC,A3 a2a
    class User user
    class T2 mcp
Loading

Chapter Guide

Chapter Key Question Outcome
01 - Getting Started What is A2A and how does it differ from MCP? Clear mental model of agent interop
02 - Protocol Specification What are the core protocol primitives? Understanding of Agent Cards, tasks, and messages
03 - Agent Discovery How do agents find and evaluate each other? Ability to publish and consume Agent Cards
04 - Task Management How does the full task lifecycle work? Mastery of task creation, streaming, and artifacts
05 - Authentication and Security How do agents trust each other? Secure agent communication patterns
06 - Python SDK How do I build A2A agents in Python? Working A2A server and client
07 - Multi-Agent Scenarios How do agents delegate and compose? Real-world multi-agent patterns
08 - MCP + A2A How do MCP and A2A work together? Full ecosystem architecture

What You Will Learn

  • How to read and implement the A2A protocol specification
  • How to create Agent Cards that advertise capabilities and skills
  • How to manage the full task lifecycle with streaming and push notifications
  • How to authenticate and authorize agent-to-agent communication
  • How to build A2A servers and clients using the Python SDK
  • How to design multi-agent delegation and composition patterns
  • How to combine MCP (tools) and A2A (agents) into a unified architecture

Source References

Related Tutorials

Start with Chapter 1: Getting Started.

Navigation & Backlinks

Full Chapter Map

  1. Chapter 1: Getting Started
  2. Chapter 2: Protocol Specification
  3. Chapter 3: Agent Discovery
  4. Chapter 4: Task Management
  5. Chapter 5: Authentication and Security
  6. Chapter 6: Python SDK
  7. Chapter 7: Multi-Agent Scenarios
  8. Chapter 8: MCP + A2A

Generated by AI Codebase Knowledge Builder