Purple AI

What is A2A protocol?

Infographic: The A2A Protocol

The Agent-to-Agent (A2A) Protocol

Unlocking True AI Collaboration

The "N x M" Problem

As specialized AI agents become common, making them work together is complex. Without a standard, each connection is a custom, fragile integration, creating a chaotic and unscalable system.

BEFORE A2A: Tangled Integrations

Agent A
Agent B
X
Agent Y
Agent Z

Result: A messy web of point-to-point connections.

AFTER A2A: A Universal Standard

Agent A
Agent B
✅
Agent Y
Agent Z

Result: A single protocol enables seamless collaboration.

How It Works: Core Architecture

A2A uses a client-server model built on standard web technologies. A host agent discovers and delegates tasks to specialized remote agents using a standardized "Agent Card."

👤

Host Agent

(A2A Client)

Initiates request and delegates sub-tasks.

📇

Agent Card

(JSON File)

A digital "business card" detailing an agent's skills.

⚙️

Remote Agent

(A2A Server)

Listens for requests and performs specialized tasks.

Core Capabilities

The protocol enables rich, structured interactions through four foundational capabilities.

🔍 Capability Discovery

Agents can publish their skills via their Agent Card, allowing other agents to find them and understand their functions.

📋 Task Management

Communication is task-oriented. A client agent can assign a task to a remote agent and monitor its progress.

🤝 Collaboration

The protocol defines how agents exchange messages, share context, and pass artifacts like files or structured data.

🎨 UX Negotiation

Agents can negotiate the format for displaying information, ensuring a smooth user experience.

A2A and MCP: The Full Picture

A2A and MCP are complementary, not competing. A2A enables agent-to-agent collaboration (horizontal), while MCP equips each agent with tools and data (vertical).

Example Workflow: Trip Planning

A primary agent uses A2A to delegate tasks to specialized agents, who in turn may use MCP to access the data they need to complete their work.

  1. 1
    User Request: A user asks their primary AI assistant to "Plan a team offsite to Lisbon."
  2. 2
    A2A Delegation: The primary agent uses A2A to task a specialized "Travel Agent" with finding flights.
  3. 3
    MCP in Action: The Travel Agent uses MCP to connect to a real-time flight data API to get options and prices.
  4. 4
    Collaboration & Consolidation: The Travel Agent reports its findings back via A2A. The primary agent consolidates this with hotel and activity info from other agents to present a complete plan.