Over the past few months, I’ve been exploring how AI agents are moving from isolated demos to real, production-grade systems. What’s making that possible is the emergence of a new foundational layer, the Agent Development Kit (ADK), supported by the Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication.

The easiest way to understand this is, like how SDKs helped developers build software applications, ADK does something similar for AI, but instead of building apps, you’re building agents that can act, collaborate, and reason across systems.

And the real benefit comes when you combine ADK with:
👉 MCP, that ensures that agents retain and share context consistently, even as they move between models or tasks.
👉 A2A, that allows these agents to talk to each other, passing insights, delegating work, and completing workflows together.

I believe that this combination of ADK + MCP + A2A is quietly redefining how multi-agent systems are designed. More importantly, it’s helping teams move proof-of-concepts to production faster and at lower cost, because the orchestration, context management, and communication layers are already built in.

Let us take a simple example, hiring automation for recruitment, to explain this.

With ADK, you can design specialized agents for each stage: resume screening, interview scheduling, feedback collection, and offer generation.
◾ ADK provides the structure to build and orchestrate these agents.
◾ MCP ensures every agent operates with shared context such as a candidate’s details, interview notes, and communication history.
◾ A2A enables these agents to coordinate, for example, the screening agent handing shortlisted candidates to the scheduling agent automatically.

What you get is not another chatbot but a coordinated, context-aware system that handles repetitive work autonomously, freeing recruiters to focus on decisions that matter.

And because this setup sits on a well-defined architecture, teams can transition from POC to production with far less engineering overhead and significantly lower cost than traditional one-off integrations.

Read more: https://google.github.io/adk-docs/agents/