A2A Protocol - Agent2Agent (A2A) Protocol Resources

Welcome to the A2A Protocol resources website. Here you'll find everything you need to know about the Agent2Agent(A2A) Protocol, including documentation, tutorials, and a list of supported AI agents.

Resources

Explore various resources for the A2A Protocol to help you get started and integrate.

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Official Website

Visit the official A2A Protocol website for the latest updates and announcements.

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Tutorials

Step-by-step guides to help you understand and implement the A2A Protocol.

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Documentation

Comprehensive documentation covering all aspects of the A2A Protocol.

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What is A2A Protocol?

Learn about the Agent2Agent (A2A) Protocol and how it enables communication between AI agents.

The Agent2Agent (A2A) Protocol is an open standard initiated by Google designed to enable communication and interoperability between disparate AI agent systems.

The core goal is to allow agents built on different frameworks or by different vendors to discover each other's capabilities, negotiate interaction modes, and collaborate on tasks.

A2A Protocol Diagram

Key Features

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Agent Discovery

Agents can discover each other's capabilities through Agent Cards.

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Task Management

Standardized task lifecycle with clear states and transitions.

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Multiple Content Types

Support for text, files, and structured data exchange between agents.

Real-time Updates

Streaming updates for long-running tasks and real-time collaboration.

A2A vs MCP: Understanding the Difference

Learn how the Agent2Agent Protocol (A2A) and Model Context Protocol (MCP) complement each other in the AI ecosystem.

A2A and MCP serve different but complementary purposes in the AI agent ecosystem:

A2A Protocol Focus

A2A

A2A enables communication between different AI agents, allowing them to collaborate, share information, and coordinate actions regardless of their underlying frameworks or vendors.

Key Features:

  • Agent Discovery
  • Task Management
  • Multiple Content Types
  • Real-time Updates

MCP Protocol Focus

MCP

MCP (Model Context Protocol) provides tools and context to individual agents, enhancing their capabilities by giving them access to external tools, data sources, and APIs.

Key Features:

  • Tool Calling
  • Context Augmentation
  • API Integration
  • Data Retrieval

Complementary Nature

A2A and MCP work in parallel: MCP enhances individual agent capabilities, while A2A enables those agents to work together effectively. They are not competing standards but complementary technologies that address different aspects of agent functionality.

A2A

Agent-to-Agent Communication

MCP

Agent-to-Tool Communication

AI Agents