Why Every Developer Needs to Know About Google's Agent2Agent Protocol

Imagine if AI agents could collaborate seamlessly, no matter who built them. Google's Agent2Agent Protocol (A2A) is making that a reality—and it’s poised to redefine AI development.

What I Discovered About A2A

I dove into Google’s recently launched Agent2Agent Protocol (A2A), an open standard that enables AI agents to communicate and coordinate across diverse frameworks and vendors. Announced on April 9, 2025, A2A addresses a critical pain point in enterprise AI: getting specialized agents from different ecosystems to work together without clunky integrations. This matters because, as AI becomes integral to business workflows, interoperability is no longer optional—it’s essential.

While A2A and MCP address different aspects of AI interoperability, they are complementary. A2A handles the communication between AI agents, enabling them to coordinate and delegate tasks. MCP, on the other hand, provides these agents with standardized access to the tools and data they need to perform their functions. Together, they facilitate the development of sophisticated, agent-based AI systems capable of complex, coordinated actions.

Link to MCP article: https://www.linkedin.com/pulse/why-every-developer-needs-know-anthropics-model-context-perisic-vqvhf/

The Core of A2A

A2A is built on familiar standards like HTTP, JSON-RPC, and SSE, ensuring compatibility with existing enterprise systems. Its key features include:

• Capability Discovery: Agents share their abilities via an “Agent Card” in JSON format, enabling automated service discovery.
• Task Management: Supports both short tasks, like booking a meeting, and long-running processes, like candidate sourcing, with real-time status updates.
• Secure Collaboration: Offers enterprise-grade authentication and end-to-end encryption, ensuring safe agent interactions.
• Multimodal Support: Handles text, forms, audio, and video streaming, making it versatile for varied use cases.

For example, consider a hiring workflow where one agent sources candidates from platforms like LinkedIn, another schedules interviews, and a third conducts background checks. A2A allows these agents to exchange data and coordinate actions seamlessly, delivering a unified process.

Why This Is a Game-Changer

A2A’s significance lies in its potential to break down silos in AI development. Developers are no longer tethered to a single vendor’s ecosystem. Instead, they can build agents that interoperate with others, fostering innovation and flexibility. This is particularly impactful in enterprises where multiple AI solutions coexist—think Salesforce, SAP, and custom-built agents all working in harmony.

The protocol’s adoption by over 50 major partners, including Atlassian, PayPal, Salesforce, and SAP, signals strong industry backing. Prakhar Mehrotra, SVP & Head of Artificial Intelligence at PayPal, noted, “PayPal supports Google Cloud’s A2A protocol, which represents a new way for developers and merchants to create next-generation commerce experiences, powered by agentic AI” (Google Developers Blog). Similarly, Dallas Dolen, Global Google Cloud Alliance Leader at PwC, emphasized, “At PwC, we believe the future of enterprise AI lies in seamless collaboration—not just between people and systems, but between agents themselves.”

A2A complements Anthropic’s Model Context Protocol (MCP), which standardizes how AI models connect to tools and data. If MCP is the “USB-C for AI integrations,” as described by Addy Osmani (AI Agents Overview), A2A is the lingua franca for agent collaboration, enabling dynamic, multimodal communication without shared memory or resources.

The Bigger Picture

The rise of A2A points to a broader trend: AI is moving beyond isolated chatbots to interconnected ecosystems. Just as HTTP standardized web communication, A2A could become the backbone of multi-agent systems, lowering barriers for businesses to mix and match agents. This interoperability is critical as AI agents take on more complex tasks, from automating supply chains to enhancing customer support. For developers, mastering A2A means staying ahead in a world where collaborative AI is the new standard.

Getting Started with A2A

A2A is open source, with its specification, sample code, and examples available on GitHub. Developers can experiment with integrations for frameworks like Google’s Agent Development Kit (ADK), LangGraph, and CrewAI. A demo video showcases how A2A enables seamless communication between agents (Maginative Article). The protocol is still evolving, with a production-ready version slated for later in 2025, but early adopters can contribute via the A2A Community.

More details:

• https://github.com/google/A2A
• https://developers.googleblog.com/en/a2a-a-new-era-of-agent-interoperability/
• https://github.com/pab1it0/awesome-a2a
• https://github.com/pab1it0/google-maps-a2a (Google Maps A2A Server)
• https://huggingface.co/blog/lynn-mikami/agent2agent (read more on huggingface)
• https://www.youtube.com/watch?v=voaKr_JHvF4 (if you like visual explanation)