Agent-to-Agent (A2A) Protocol

A2A enables AI agents to communicate with each other, securely exchange information, and coordinate actions across different platforms and frameworks. Unlike MCP which connects agents to data sources, A2A enables agents to collaborate as peers, sharing tasks and coordinating complex multi-step operations.

This visual was inspired by documentation from Google and was created by the Black Kite Data Research team.

How It Works

The Agent-to-Agent (A2A) protocol lets autonomous agents hand off tasks over plain HTTP: each message is a JSON-RPC envelope that carries a Task, optional streamed Artifact, and OAuth-scoped metadata, so one agent can discover another via its .well-known/agent.json card, send the task, and receive results in real time. In practice this means a threat-intel agent can trigger a vendor-risk agent just by posting a signed task object—no custom web-hooks or shared memory needed.

Code element	What A2A expects	Narrative for Readers
agent_card.json	Standardized capability advertisement via Agent Cards containing endpoints, authentication, and available services	Think of this as an agent's business card - it tells other agents "here's what I can do and how to reach me"
task_lifecycle	Structured task states: pending → in-progress → completed/failed with unique Task IDs	Like a project management system for agents - every collaboration has clear status tracking
secure_communication	JSON-RPC 2.0 over HTTPS with enterprise authentication (OAuth, mutual TLS)	Agents talk to each other like secure web services, not like informal chat
message_parts[]	Rich content exchange including text, files, artifacts with content-type negotiation	Agents can share anything from text responses to generated reports, images, or structured data
capability_discovery	Dynamic agent discovery and service registry for finding specialized agents	Like a phone book for agents - "I need a financial analysis expert" → finds and connects to appropriate agent

Use Case

The Challenge: Coordinated APT Campaign Detection

A sophisticated nation-state actor launches coordinated attacks across multiple organizations in the financial sector. Traditional threat hunting relies on each organization's isolated analysis, missing the broader campaign pattern.

The A2A-Enabled Solution:

Network Behavior Agent (Bank A) detects anomalous traffic patterns

Attribution Agent (Shared Intel Hub) receives IOCs for analysis

Malware Analysis Agent (Bank B) analyzes related samples

Campaign Correlation Agent synthesizes findings across all participants

All participating agents receive coordinated threat intelligence

Why A2A specifically for this use case ?

This scenario requires specialized agents to collaborate and coordinate their findings in real-time across organizational boundaries. MCP would only handle data access within each organization, and LCEL would orchestrate workflows within a single system, but only A2A enables secure, peer-to-peer agent collaboration where each agent maintains its expertise while contributing to collective defense.

Key Benefits:

Cross-organizational intelligence sharing without exposing internal systems
Specialized agents coordinate (network analysis + malware analysis + attribution)
Real-time collaboration as threats evolve
Maintains autonomy while enabling collective defense