A single AI assistant can do a lot. But some work is genuinely too large, too varied, or too parallel for one agent to handle end-to-end. Agent-to-agent (A2A) protocols define how AI agents can hand tasks to each other — breaking complex work into pieces, routing each piece to the agent best suited to handle it, and assembling the results. Understanding A2A helps clarify what is actually possible when AI systems are described as "agentic."
What "agent-to-agent" means
An AI agent is a system that takes a goal and works toward it — using tools, making decisions, and taking actions over a series of steps. A2A is about what happens when those agents need to work together.
In a typical A2A setup, one agent acts as a coordinator. It receives a complex task — one that requires multiple different capabilities or that benefits from running in parallel — and breaks it into pieces. Each piece is handed to another agent suited for that sub-task. Those agents work on their pieces, return results, and the coordinator assembles the final output.
This mirrors how work is organised in a well-run team: a project manager who understands the whole task, and specialists who handle the parts they know best.
Why one agent isn't always enough
A single AI agent faces practical limits. It can only work sequentially on one thing at a time, its context is bounded, and it may not be specialised for every sub-task in a complex job.
Consider a task like "prepare a market briefing for this sector, translated into three languages, with a risk summary attached." A single agent could do this, but it would take time and would likely be weaker on the translation than a dedicated language agent. With A2A, the research, the risk analysis, and each translation can run in parallel, handled by agents built for those specific jobs. The result is faster and often better.
How A2A differs from simply calling a tool
When an agent uses MCP to call a tool, it is invoking a defined function and receiving a structured result. The tool does not have goals, memory, or the ability to take its own decisions — it just executes and returns.
A2A is different. The agents involved can themselves have goals, can make decisions, can use their own tools, and can take multiple steps. The coordinator is not just calling a function; it is delegating to another capable system. That distinction matters for complex, open-ended work.
Interoperability and open standards
Like MCP, A2A is most useful when it is an open standard rather than a proprietary interface. When agents from different developers can talk to each other because they share a common protocol, the ecosystem of capable agents grows much faster than any one team could build on its own.
Google has published an open Agent-to-Agent protocol specification, and other organisations are contributing to the space. The direction is toward a world where agents from different sources can be composed together — not a world where every combination requires bespoke integration.
How askFinz relates to A2A
askFinz's agents and protocols are built around these emerging standards. When you ask askFinz to handle a task that spans multiple capabilities, A2A is part of what makes that possible — coordinating the work across the relevant agents and returning a coherent result.
The goal is that you describe what you want, not which agents should handle which parts. The platform routes accordingly.
What this means for users
You do not need to understand A2A to benefit from it. The practical effect is that complex, multi-step tasks complete faster and more reliably. A briefing that requires research, summarisation, translation, and formatting does not need to be broken into four separate requests — you ask once, and the system coordinates the rest.
As A2A standards mature and more agents adopt them, the range of tasks that can be handled this way will grow. The infrastructure is being built now, and the capability gains will compound over time.
Further reading
- How askFinz connects to external agents and protocols: Protocols.
- AI agents in the askFinz platform: Agents.
- How MCP and A2A relate as complementary open standards: What is MCP (Model Context Protocol)?.