Definition
A2A Protocol Explained: How Agents Communicate Across Systems
The Agent2Agent protocol is a standard for agent-to-agent communication, delegation, and result exchange across systems, especially when one agent needs another agent to do part of the work.
Direct answer
The Agent2Agent (A2A) protocol is a way for one agent to discover, hand off to, and receive work from another agent. It matters when workflows cross agent boundaries and coordination becomes a real systems problem rather than just a prompt design problem.
Why it matters now
As teams move from one agent to many, the hard part stops being "can a model call a tool?" and becomes "how do agents communicate safely across systems?"
That is the space A2A is trying to address:
- discovery
- delegation
- capability description
- trust and authentication
- result exchange across boundaries
What problem it solves
Tool access and agent coordination are not the same thing.
If a model needs to read a file, query a database, or use a CRM connector, that is a tool integration problem.
If one agent needs to pass a task to another specialist agent, that is an interoperability problem.
A2A focuses on the second case.
How it works in plain English
The protocol gives agents a shared way to describe:
- what they can do
- how to contact them
- what kind of inputs they accept
- what status or results they return
In practice, that makes it easier for a planner, coordinator, or calling agent to delegate cleanly instead of improvising brittle free-text handoffs.
A2A vs MCP
| Question | Better fit |
|---|---|
| How does an AI system connect to tools or data? | MCP |
| How does one agent delegate work to another agent? | A2A |
| Do we need both? | sometimes |
The important distinction is simple:
- MCP is about tools and context access
- A2A is about agent-to-agent coordination
When teams actually need it
You probably do not need A2A when:
- one agent can do the job
- the workflow is really just a tool chain
- the coordination overhead would outweigh the benefit
You start to need it when:
- specialist agents own different domains
- agents span vendors or trust boundaries
- one system needs to broker work across several autonomous components
Trust and security questions
Interoperability creates new problems:
- who is allowed to call which agent
- how capabilities are described and verified
- how results are authenticated
- how failures and escalation are handled
That is why protocol adoption without governance is incomplete.
Common misconceptions
"A2A replaces MCP"
No. They solve different layers of the stack.
"Every team needs A2A now"
No. Small workflows often work better with plain orchestration and clear tool use.
"Agent interoperability is mostly a protocol naming issue"
No. The real challenge is trust, identity, ownership, and operational clarity.
FAQ
Do small teams need A2A?
Usually not at first. Many teams should start with simpler workflow orchestration.
Is A2A only useful across vendors?
No. It can matter inside one organization if multiple agents need to coordinate cleanly.
How is capability advertised?
Through structured capability descriptions, not just free-text prompts.
Is A2A the same as multi-agent prompting?
No. Prompting is a local instruction technique. A2A is a protocol for inter-agent communication.
Related AIReady guides
- MCP Explained for Teams
- What is Model Context Protocol (MCP)?
- Single-Agent vs Multi-Agent Systems
- Why Most AI Agents Are Really Workflows
Sources
Refresh checklist
- review protocol and spec changes
- update the MCP comparison if vendor support shifts
- recheck governance assumptions as interoperability patterns mature
Last updated: March 18, 2026
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