Use A2A to Connect Agents Across Different Frameworks and Teams

Why It Matters

Standardizing agent‑to‑agent communication cuts integration costs and accelerates deployment of complex AI ecosystems across industries.

Key Takeaways

• A2A standardizes agent discovery and communication
• Course covers ADK, LangGraph, BeeAI integration
• Open protocol now under Linux Foundation governance
• Enables sequential and hierarchical multi-agent workflows
• Complements MCP by linking agents directly

Pulse Analysis

The rapid rise of autonomous, agentic AI systems has outpaced the tools needed to make them work together. Different development frameworks—each with its own APIs and data models—create silos that force engineers to write bespoke adapters. The Agent2Agent (A2A) protocol emerged from Google Cloud’s internal research and has been elevated to an open, Linux‑Foundation‑governed standard, offering a universal language for agents to discover peers, negotiate contracts, and exchange messages securely. By abstracting the underlying transport and lifecycle details, A2A reduces friction and enables rapid prototyping of heterogeneous AI teams.

The new short course leverages this emerging standard to teach practical, end‑to‑end skills. Participants build a healthcare‑focused multi‑agent workflow, exposing agents built with ADK, LangGraph, and BeeAI as A2A‑compliant servers. They then create client applications that orchestrate these agents into sequential and hierarchical processes, deploying the entire stack on open‑source infrastructure. The curriculum also highlights how A2A integrates with the Managed Cloud Platform (MCP), which connects agents to external data sources, thereby completing a full stack for enterprise AI solutions.

For businesses, adopting A2A means faster time‑to‑value for AI initiatives and lower engineering overhead. As more vendors and open‑source projects adopt the protocol, a growing ecosystem of interoperable agents will emerge, fostering innovation in sectors ranging from healthcare to finance. The synergy between A2A and MCP positions organizations to build modular, scalable AI architectures that can evolve alongside regulatory and market demands, making the protocol a strategic asset for future‑proof AI deployments.

Original Description

Learn more: https://bit.ly/4anVtk6

Announcing a new short course, A2A: The Agent2Agent Protocol, built in collaboration with Google Cloud and IBM Research.

As agentic systems grow more complex, connecting agents built with different frameworks often means writing custom integrations. A2A is an open protocol that standardizes how agents discover each other and communicate, making cross-framework collaboration far easier. Originally introduced by Google Cloud and now stewarded by the Linux Foundation, A2A is quickly becoming a shared standard for agent collaboration.

In this hands-on course, you’ll build a healthcare multi-agent system using agents created with different frameworks. You’ll expose agents as A2A servers, create A2A clients, and orchestrate agents into sequential and hierarchical workflows. You’ll also see how A2A complements MCP: while MCP connects agents to external data systems, A2A enables agents to work with each other.

You’ll learn how to:

- Implement A2A’s client-server architecture, including agent cards and lifecycle concepts

- Expose agents built with ADK, LangGraph, or BeeAI as A2A-compliant servers

- Create A2A clients to connect and coordinate agents across frameworks

- Orchestrate multi-agent workflows dynamically and deploy them using open-source infrastructure

The course is taught by Holt Skinner, DevRel at Google, Ivan Nardini, AI/ML DevRel at Google, and Sandi Besen, Ecosystem Lead at IBM Research.

Enroll now: https://bit.ly/4anVtk6