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Build Anything With A2A Agent - Here's How

2 min read

Build Anything With A2A Agent - Here’s How

AI Summary

Summary of A2A (Agent-to-Agent) Communication Protocol

  1. Introduction
    • Overview of the importance of Google’s open-sourcing of the Agent-to-Agent (A2A) protocol at Google Cloud Next 2025.
    • Explanation of how A2A enables different AI agents to communicate despite using various technologies.
  2. Purpose of A2A
    • Facilitates seamless collaboration among AI agents across different frameworks (e.g., LangChain, Crew AI).
    • Acts as a common language for agents, allowing for enhanced interoperability.
  3. Demo Overview
    • Description of a multi-agent system for trip planning.
    • Agents involved: Weather Agent, Hotel Agent, Activity Agent.
    • Orchestrator connects these agents to create comprehensive travel plans.
  4. Implementation Challenges
    • Issues with API calls and dependencies (httpx, Pydantic, FastAPI).
    • Error handling mechanisms to manage service availability and unexpected formats.
  5. Agent Communication Mechanism
    • Agents can request and share information without human intervention (e.g., sales AI consulting finance AI).
    • Visual analogy of movie production teams to illustrate roles within A2A.
  6. Distinction Between A2A and MCP (Multi-Agent Collaboration)
    • A2A for agent communication, while MCP facilitates access to tools and resources.
    • They complement each other in creating a robust agent ecosystem.
  7. Technical Implementation Using Python
    • Creation of three agent classes: Weather, Hotel, and Activity.
    • Each agent handles requests and responses based on localized databases (New York, Tokyo).
    • Use of agent cards (JSON files) to define agent capabilities.
    • Example setup of server ports: Weather (501), Hotel (502), Activity (503).
  8. Collaborative Trip Planning
    • Orchestrator connects to the three agent services using asynchronous Python.
    • Error handling throughout the process to ensure a robust user experience.
    • Assembly of a final travel plan with details from all agents.
  9. Future Implications
    • A2A protocol is in early stages but holds promise for establishing standards in agent interoperability.
    • Encouragement for community contribution to develop and enhance the A2A standard.

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