Intermediate

A2A: The Agent2Agent Protocol

Instructors: Holt Skinner, Ivan Nardini, Sandi Besen

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Earn an accomplishment with PRO · Updated Feb 11, 2026

  • Intermediate
  • 13 Video Lessons
  • 1 Code Example
  • Earn an accomplishment with PRO
  • Updated Feb 11, 2026
  • Instructors: Holt Skinner, Ivan Nardini, Sandi Besen
  • Google CloudGoogle CloudIBM ResearchIBM Research
  • Learn more aboutMembership PRO Plan

What you'll learn

  • Expose agents built with frameworks like Google ADK, LangGraph, or BeeAI as A2A servers to make them A2A-compliant.

  • Create A2A clients from scratch or by using A2A integrations to connect to A2A-compliant agents.

  • Orchestrate A2A-compliant agents into sequential and hierarchical workflows.

Course recap

PRO

This course teaches how to build and run agents that communicate through the Agent2Agent (A2A) protocol, the emerging industry standard for multi-agent collaboration. Built in partnership with Google Cloud and IBM Research, it covers the protocol architecture, hands-on implementation of A2A servers and clients, and integration with complementary protocols like MCP.

Concept map

Concepts in A2A: The Agent2Agent Protocol and the courses that connect to themA2A: The Agent2Agent ProtocolA2A: The Agent2Agent Prot…Agent2Agent protocolAgent CardModel Context ProtocolTask lifecycleConditional RequirementsAI Agents in LangGraphAI Agentic Design Patterns with AutoGenAI Agentic Design Pattern…Build AI Apps with MCP Server Working with Box FilesBuild AI Apps with MCP Se…Agentic AIBuilding Agentic RAG with LlamaIndexBuilding Agentic RAG with…Agent Skills with AnthropicAgent Skills with Anthrop…Concepts in A2A: The Agent2Agent Protocol and the courses that connect to themA2A: The Agent2Agent ProtocolA2A: The Agent2…Agent2Agent protocolAgent2Agent pro…Agent CardModel Context ProtocolModel Context P…Task lifecycleConditional RequirementsConditional Req…

Key concepts

  • Agent2Agent protocolAn open-source, community-governed protocol (under the Linux Foundation) that standardizes how agents discover and communicate with each other, regardless of framework or model
  • Agent CardA JSON document (hosted at `.well-known/agent-card.json`) that serves as a digital business card describing an agent's capabilities, endpoint, authentication, and skills
  • Model Context ProtocolComplementary to A2A; MCP connects agents to tools while A2A connects agents to peer agents
  • Task lifecycleA2A tasks go through states: submitted, working, input-required, completed, or failed
  • Conditional RequirementsBeeAI framework's declarative rule-based constraints that enforce agent behavior at the framework level rather than via system prompts

Lesson highlights

  1. 1.Introduction — Overview of A2A and the healthcare multi-agent system
  2. 2.Why Agent2Agent Protocol? — Open standards, A2A vs MCP, use cases
  3. 3.A2A Architecture — Agent cards, messages, tasks, artifacts, execution modes (sync/async/streaming/push)
  4. 4.Building a QA Agent with Claude on Vertex AI — Insurance policy agent using Anthropic
  5. 5.Wrapping the QA Agent into an A2A Server — AgentExecutor, AgentSkill, AgentCard, Starlette server
  6. 6.Calling an A2A Agent using an A2A Client — HTTP client, message handling, task handling
  7. 7.Creating an A2A Health Research Agent using Google ADK — Gemini with built-in Google search
  8. 8.Creating an A2A Sequential Chain Agent with ADK — RemoteA2Aagent, SequentialAgent
  9. 9.Creating an A2A Healthcare Provider Agent using LangGraph and MCP — MCP server for doctor data
  10. 10.Creating an A2A Client using Microsoft Agent Framework — Cross-framework interoperability
  11. 11.Creating a Multi-Agent System using A2A with BeeAI Framework — RequirementAgent, HandoffTool, ConditionalRequirements
  12. 12.Running A2A Agents on Agent Stack — Open-source deployment platform by IBM Research
  13. 13.Advanced A2A Concepts — Security (TLS, OAuth), extensions, distributed tracing with OpenTelemetry
  14. 14.Conclusion

About this course

Join this new short course on A2A: The Agent2Agent Protocol, built in partnership with Google Cloud and IBM Research, and taught by Holt Skinner, Ivan Nardini, and Sandi Besen.

Connecting agents built with different frameworks typically requires extensive custom integration. A2A provides an open protocol that standardizes how agents discover each other and communicate. Launched by Google Cloud in April 2025 and donated to the Linux Foundation, with IBM’s Agent Communication Protocol merging shortly after, A2A is emerging as the industry standard for agent collaboration.

In this course, you’ll build a healthcare multi-agent system with three specialized agents using different frameworks. You’ll wrap each agent in an A2A server, build A2A clients to communicate with them, and orchestrate them into sequential and hierarchical workflows. You’ll see how A2A complements MCP: while MCP connects agents to external data systems, A2A enables agents to collaborate with each other.

In detail, you’ll:

  • Understand why A2A standardizes agent communication and explore its client-server architecture, including agent cards and the agent lifecycle.
  • Build an insurance policy agent using Claude Haiku 4.5 on Vertex AI, wrap it in an A2A server using the A2A Python SDK, and create an A2A client to communicate with it.
  • Build a health research agent using Google Agent Development Kit and Gemini 3 Pro that performs research with Google Search.
  • Chain agents sequentially using ADK, where one agent’s output feeds into the next through A2A.
  • Create a healthcare provider agent with LangGraph, connect it to an MCP server, and interact with it using Microsoft Agent Framework’s A2A client.
  • Orchestrate multiple agents dynamically with BeeAI Framework, using the Requirement Agent to delegate tasks to specialized agents as needed.
  • Deploy your A2A agents to BeeAI’s Agent Stack , an open-source infrastructure for deploying and sharing A2A agents.

Whether you’re orchestrating agents within your organization or collaborating across different teams, this course gives you hands-on experience with the protocol standardizing how agents work together.

Who should join?

AI developers building multi-agent systems or working with agentic workflows. Familiarity with Python and basic understanding of AI agents recommended.

Course Outline

13 Lessons・1 Code Examples
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Instructors

Holt Skinner

Holt Skinner

Developer Advocate, Cloud AI at Google

Ivan Nardini

Ivan Nardini

Sandi Besen

Sandi Besen

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