Agent-to-Agent: The Protocol LLM Agents Need to Finally Talk to Each Other

· origo's blog

Ever tried getting AI agents from different frameworks to work together? It's like herding cats that speak different languages. Your LangChain agent can't talk to your CrewAI agent, and your custom solution doesn't play nice with either of them.

This fragmentation isn't just annoying—it's the major roadblock keeping us from building truly powerful multi-agent systems. But there's a solution on the horizon, and Google is leading the charge.

The Problem: Agent Babel #

Imagine trying to organize a conference call where each participant speaks a different language and uses a different phone system. That's the current state of AI agent communication.

A recent paper (Apr 25 2025), "A Survey of AI Agent Protocols", perfectly captures this challenge. The researchers highlight how the absence of standardized communication methods is severely limiting what our increasingly capable agents can accomplish together.

Each framework has its own way of:

This means your sophisticated agents end up isolated in their own little worlds, unable to combine their capabilities. Not ideal when the real power of agents comes from collaboration.

What Are Agent Protocols Anyway? #

Agent protocols are standardized communication frameworks that define how agents talk—both to external systems and to each other. Think of them as the grammar rules for agent conversations.

Drawing from the classification system outlined in the research paper, these protocols come in two main flavors:

And they can be either:

If this sounds abstract, here's what matters: we need these protocols if we want agents to work together at scale.

Enter A2A: Google's Solution to Agent Communication #

Agent-to-Agent (A2A) is Google's open protocol initiative designed to be the common language for AI agents. It doesn't matter which framework or vendor built them—agents using A2A can collaborate seamlessly.

What makes A2A particularly interesting is its focus on enterprise-grade collaboration. This isn't just a toy protocol for simple chatbots. It's designed for serious business applications where security, reliability, and traceability matter.

According to the researchers' classification, A2A is a general-purpose inter-agent protocol—precisely what's needed to enable the kind of flexible, scalable collaboration that complex systems require.

Why A2A Stands Out from the Crowd #

1. Surprisingly Simple (By Design) #

Rather than reinventing the wheel, A2A leverages existing standards:

This makes A2A far easier to adopt than protocols requiring entirely new infrastructure.

2. Built for the Enterprise (Not Just Demos) #

A2A comes with built-in considerations for:

It treats agents as professional tools, not science projects.

3. Async-First Architecture #

A2A is centered around the concept of a Task—not just quick exchanges. This means it handles:

This async-first approach mirrors how real work happens in organizations.

4. Handles Any Content Type You Throw At It #

The protocol works natively with:

No more cobbling together solutions for different content types.

5. Privacy by Default #

A2A embraces "opaque execution" where agents share results without revealing their internal thoughts, plans, or tools. This means:

You get collaboration without compromising your secret sauce.

A2A's Building Blocks: The Core Concepts #

Agent Card #

Think of this as your agent's LinkedIn profile—a metadata file (typically at /.well-known/agent.json) that describes:

This enables dynamic discovery and connection between agents.

Task #

The fundamental work unit in A2A:

Message #

Communication turns between agents, with clear roles:

Part #

The atomic content units in messages:

Artifact #

The outputs generated during a task:

These building blocks combine to create a flexible yet structured way for agents to collaborate.

A2A in Action: How Agents Actually Talk #

The typical A2A conversation flow looks like this:

  1. Discovery: "Hey, what can you do?" (Client fetches Agent Card)
  2. Initiation: "I need help with X" (Client sends task request)
  3. Processing: (Server handles the task, possibly streaming updates)
  4. Interaction: "Can you clarify Y?" (Additional messages if needed)
  5. Completion: "Here's the result" (Task reaches terminal state)

This pattern supports everything from simple requests to complex multi-turn collaborations.

Why This Matters: The Trip Planning Example #

Let's see how A2A changes the game with a practical example: planning a trip.

Without A2A: A central agent has to individually call flight services, hotel services, and weather services as tools, coordinating every single interaction.

With A2A: Specialized agents (Transportation, Accommodation, Weather) communicate directly when needed. The Flight Agent can ask the Weather Agent about conditions directly, while a coordinator agent focuses on the big picture.

This direct agent-to-agent communication pattern is far more efficient and scalable than having every interaction pass through a central coordinator.

The research paper examines this exact scenario, comparing different protocol approaches. A2A's design enables what the authors describe as "complex collaboration between agents within an enterprise"—a more flexible and natural communication pattern than centralized or overly formalized alternatives.

Getting Your Hands on A2A #

A2A is open source and ready for you to try. The project offers:

If you're building agent systems, A2A offers a ready-made solution to the communication problem.

Shape the Future of A2A #

A2A is actively evolving, and this is where you can make your mark. The roadmap includes exciting improvements, and the community needs contributors like you to help build them:

Protocol Evolution #

Ways to Contribute #

The history of tech is clear: people who shape protocols end up shaping the future. Getting involved now positions you as an expert in what could become the standard for agent communication.

Check out the A2A GitHub repository to find where your skills can make the biggest impact. Whether you're a coder, writer, designer, or just an enthusiast, there's room for your contribution.

Why You Should Care #

If you're building AI systems with multiple agents, communication protocols aren't just nice-to-have—they're essential infrastructure.

As the researchers behind "A Survey of AI Agent Protocols" emphasize, the development of standardized protocols is critical for enabling collective intelligence among AI systems. A2A represents one of the most promising steps in this direction.

A2A gives you a standardized way for your agents to:

Instead of reinventing basic communication patterns, you can focus on what makes your agents actually useful.

The future of AI isn't just smarter individual agents—it's about how they work together. A2A is paving the way for that collaborative future, one protocol message at a time.