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Agent Development Kit

Agent Development Kit (ADK) is a flexible and modular framework for developing and deploying AI agents. While optimized for Gemini and the Google ecosystem, ADK is model-agnostic, deployment-agnostic, and is built for compatibility with other frameworks. ADK was designed to make agent development feel more like software development, to make it easier for developers to create, deploy, and orchestrate agentic architectures that range from simple tasks to complex workflows.

News: ADK Go 1.0.0 released!

ADK Go 1.0.0 release adds several major features, including OpenTelemetry integration, self-healing logic using plugins, and improved human input support. For more details on this release, see the ADK Go v1.0 announcement.

News: ADK Java 1.0.0 released!

ADK Java 1.0.0 is now available! This release includes several bug fixes and enhancements. Read more about it in the blog announcement. Upgrade to ADK Java 1.0.0 to take advantage of these enhancements and ensure optimal performance in your applications.

ADK Python Security Advisory: LiteLLM supply chain compromise

Unauthorized code was identified in LiteLLM versions 1.82.7 and 1.82.8 on PyPI on March 24, 2026. If you use ADK Python with the eval or extensions extras, update to the latest version of ADK Python immediately. If you installed or upgraded LiteLLM during this period, rotate all secrets and credentials. For details and required actions, refer to the ADK security advisory and LiteLLM's Security Update: Suspected Supply Chain Incident.

Get started:


pip install google-adk


npm install @google/adk


go get google.golang.org/adk

pom.xml
<dependency>
    <groupId>com.google.adk</groupId>
    <artifactId>google-adk</artifactId>
    <version>1.0.0</version>
</dependency>
build.gradle
dependencies {
    implementation 'com.google.adk:google-adk:1.0.0'
}

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Watch "Introducing Agent Development Kit"!

  • Flexible Orchestration

    Define workflows using workflow agents (Sequential, Parallel, Loop) for predictable pipelines, or leverage LLM-driven dynamic routing (LlmAgent transfer) for adaptive behavior.

    Learn about agents

  • Multi-Agent Architecture

    Build modular and scalable applications by composing multiple specialized agents in a hierarchy. Enable complex coordination and delegation.

    Explore multi-agent systems

  • Rich Tool Ecosystem

    Equip agents with diverse capabilities: use pre-built tools (Search, Code Exec), create custom functions, integrate 3rd-party libraries, or even use other agents as tools.

    Browse tools and integrations

  • Deployment Ready

    Containerize and deploy your agents anywhere – run locally, scale with Vertex AI Agent Engine, or integrate into custom infrastructure using Cloud Run or Docker.

    Deploy agents

  • Built-in Evaluation

    Systematically assess agent performance by evaluating both the final response quality and the step-by-step execution trajectory against predefined test cases.

    Evaluate agents

  • Building Safe and Secure Agents

    Learn how to building powerful and trustworthy agents by implementing security and safety patterns and best practices into your agent's design.

    Safety and Security