From the course: Hands-On AI: Building AI Agents with Model Context Protocol (MCP) and Agent2Agent (A2A)

A2A client and server communication flow

From the course: Hands-On AI: Building AI Agents with Model Context Protocol (MCP) and Agent2Agent (A2A)

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A2A client and server communication flow

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- [Instructor] How do an A2A Client and an A2A Server communicate with each other to execute tasks and workflows? We have earlier discussed the protocols and communication elements used. Now, let's discuss how an end-to-end workflow looks like, utilizing the protocols and the communication elements. We first have the A2A server registry. This registry can be a separate registry with its own unique URI or it can be bundled inside the A2A server itself. It contains the Agent Card for the agent. The Agent Card has the agent capabilities and the Agent URL. An A2A client wants to communicate with this specific Server Agent. As its configuration, it already knows about the URL for the registry. This is the only information it needs to know if it uses an external registry. If the Agent Card is hosted by the A2A server itself, then it needs to know the URL for each of the A2A servers it needs to communicate with. The A2A client uses the URL to the registry to fetch the Agent Card. It can also do a search across all agents in the A2A server to identify the right agent and then pull its Agent Card. From the Agent Card, the client learns about the URL where the A2A server for the target agent runs. An agent in A2A is hosted through an A2A server. This supports the standard A2A interface. This interface can additionally support the Agent Card also if a registry is not used. Using the Server Agent URL, the client agent establishes a connection with the A2A server interface. It does the message exchanges as per the protocol and sends the goal or the task to be executed. This can either follow the request response or the streaming with SSE protocol. The A2A Server interface then invokes an Agent Executor. The Agent Executor serves as the link between the A2A Server code and the actual AI Agent. The Agent Executor can either load up the AI Agent inside the A2A server itself, or it can use any other kind of protocol like REST or GRPC to integrate with the AI Agent. The AI Agent is invoked by the Agent Executor with the given goal or task. The agent then executes it and returns the results back to the Agent Executor. The results are then communicated back to the Client Agent using A2A. The Client Agent then proceeds to process the response and execute its business functions. Having discussed the A2A protocol, let's now implement a multi-agent system using A2A in the next chapter.

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