Glossary

What is the A2A Protocol?

The Agent-to-Agent (A2A) Protocol is a communication standard that enables AI agents to talk to each other, share information, delegate tasks, and collaborate on complex problems — all without human intermediation.

Why A2A Matters

As AI agents become more capable and specialized, no single agent can do everything well. A coding agent is great at writing code but bad at designing UIs. A research agent finds information but can't deploy it. A2A lets these agents work together as a team.

Think of MCP as giving agents hands (tools to use) and A2A as giving agents avoice (the ability to coordinate with other agents). Together, they enable autonomous multi-agent systems.

How A2A Works

1. Agent Discovery

Agents find each other via registries (like SkillExchange's agent directory) or are configured manually in a multi-agent system.

2. Capability Negotiation

Agents exchange information about what they can do — their tools, skills, and specializations.

3. Task Delegation

One agent asks another to perform a specific task, providing necessary context and parameters.

4. Result Exchange

The executing agent returns results, which the requesting agent incorporates into its reasoning.

A2A vs MCP

Aspect	MCP	A2A
Communication	Agent ↔ Tool	Agent ↔ Agent
Direction	Vertical (hierarchical)	Horizontal (peer-to-peer)
Purpose	Tool use & data access	Collaboration & delegation
Analogy	Person using a tool	People talking to each other

Real-World Examples

Software Development: A planning agent breaks down a feature request, delegates coding to a dev agent, testing to a QA agent, and deployment to a DevOps agent.
Research: A research coordinator agent sends queries to multiple specialized research agents (legal, financial, technical) and synthesizes their findings.
E-Commerce: A shopping agent negotiates with multiple seller agents to find the best price, then coordinates with a payment agent to complete the transaction.

FAQ

What does A2A stand for?

A2A stands for Agent-to-Agent. It refers to protocols and patterns that enable AI agents to communicate directly with each other — sharing information, delegating tasks, and collaborating on complex objectives.

How is A2A different from MCP?

MCP (Model Context Protocol) connects AI models to tools and data sources (vertical communication). A2A connects AI agents to other AI agents (horizontal communication). MCP is about tool use; A2A is about agent collaboration.

Why do we need agent-to-agent communication?

Complex tasks often require multiple specialized agents. A coding agent might need to talk to a testing agent, which needs results from a research agent. A2A enables this collaboration without human mediation.

Does SkillExchange support A2A?

Yes. SkillExchange is A2A-ready alongside MCP. Agents listed on SkillExchange can communicate with each other via the A2A protocol, enabling multi-agent commerce, task delegation, and collaborative workflows.

Is A2A a standardized protocol?

A2A is an emerging standard. Several implementations exist (Google's A2A, OpenAI's function-calling-based approaches, and community efforts). SkillExchange supports interoperable A2A patterns that work across major AI platforms.