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Google Agent Development Kit

Google Agent Development Kit AI Agent
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Overview

A modular framework for building, deploying, and managing AI agents across diverse workflows.

Google's Agent Development Kit (ADK) is an open-source framework designed to simplify the creation, deployment, and management of AI agents. Optimized for Google's Gemini models yet model-agnostic, ADK supports various agent types, including LLM-powered agents, workflow controllers, and custom agents. It offers features like multi-agent orchestration, tool integration, session management, and built-in evaluation tools. ADK facilitates flexible deployment options, including local environments, Google Cloud's Vertex AI Agent Engine, and Cloud Run, making it suitable for a wide range of AI applications.

Product overview

Capabilities, pricing and fit

Google Agent Development Kit is best understood as an agent-development framework. Build powerful multi-agent systems with Agent Development Kit (ADK).

Information as of July 30, 2026

What it can do

  • Agent application development

    Build powerful multi-agent systems with Agent Development Kit (ADK).[1]

Where it fits best

  • Developing AI agents for complex task automation and orchestration.[1]
Sources (1)
  1. Agent Development Kit (ADK) - Agent Development Kit (ADK)Official site · checked 2026-07-30

Autonomy level

83/100

Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.

Reasoning: ADK enables high autonomy through dynamic LLM-driven decision-making (LlmAgent transfer) while maintaining developer control. It supports both deterministic workflows (sequential/parallel/loop patterns) and adaptive behaviors using Gemini models. Agents can self-orchestrate tool usage, state management, and inter-agent communication, though ultimat...

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Some of the use cases of Google Agent Development Kit:

  • Developing AI agents for complex task automation and orchestration.
  • Integrating multiple agents to collaborate on multifaceted workflows.
  • Deploying AI solutions across various environments, including cloud platforms.
  • Evaluating agent performance through built-in testing and monitoring tools.
  • Extending agent capabilities with custom tools and third-party integrations.

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Popularity level: 68%

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