Google Agent Development Kit

Google Agent Development Kit (ADK) is an open framework for building hierarchical multi-agent systems that run natively on Vertex AI and Gemini models, with first-class support for the Agent2Agent (A2A) protocol so sub-agents can delegate tasks and share context across teams. Instead of hand-rolling orchestration logic, developers use ADK to define parent agents that plan and route work to specialized child agents, each with its own tools, prompts, and reasoning loop. This makes ADK a strong fit for teams already invested in Google Cloud who want a production-grade path from prototype to deployed multi-agent workflow, without stitching together separate orchestration and tool-calling layers.

Where ADK shines is coordination: a top-level Gemini-powered planner agent can spawn research agents, data-retrieval agents, and action agents, then merge their outputs into a single response. The catch for most businesses is that every one of those sub-agents still needs governed access to internal systems — CRM records, ad platform spend, support tickets, product databases — and stitching bespoke connectors into each agent quickly becomes its own engineering project. BusinessMCP.com solves that layer: connect your tools, databases, and ad platforms once to a managed MCP server, and every ADK agent in your hierarchy can call the same hosted endpoint at /api/mcp using a Bearer mcph_* key, rather than each sub-agent maintaining its own integration code.

Because the hosted MCP server is model-agnostic, teams building hierarchical multi-agent systems with Google ADK can mix Gemini-based planner agents with sub-agents powered by Claude or GPT for specific reasoning tasks, all pulling from the same unified data layer. That consistency matters when an ADK deployment spans planning agents, execution agents, and reporting agents — you want one source of truth for customer data and revenue metrics, not three different API keys and three different data freshness guarantees. The BusinessMCP business-intelligence dashboard sits on top of that same connection, giving non-engineering stakeholders visibility into what every agent in the hierarchy is actually touching, querying, and returning.

ADK is best suited to teams who need structured, auditable multi-agent orchestration on Google's stack rather than a fully autonomous, open-ended agent loop. If your use case calls for hierarchical planning with clear task delegation across Vertex AI and Gemini, ADK combined with a single hosted MCP integration lets you scale from a two-agent prototype to a fleet of specialized agents without re-plumbing data access at every step. Teams evaluating other multi-agent frameworks alongside Google ADK — including CrewAI, AutoGen, or Semantic Kernel — can use the same BusinessMCP connection across all of them, which is useful when comparing frameworks or running a hybrid stack cookieless and GDPR-friendly by design.