Google has released the Agent Development Kit (ADK), an open-source Python framework designed to simplify building, evaluating, and deploying sophisticated AI agents using code-first development principles.
The new framework applies traditional software engineering practices to AI agent creation, making it easier for developers to build everything from simple automation tasks to complex multi-agent systems. While optimized for Google's Gemini models, ADK is model-agnostic and compatible with other AI frameworks.
"ADK is a flexible and modular framework that applies software development principles to AI agent creation," Google explains in the project documentation. "It is designed to simplify building, deploying, and orchestrating agent workflows, from simple tasks to complex systems."
One of ADK's standout features is its rich tool ecosystem. Developers can utilize pre-built tools, custom functions, OpenAPI specifications, or Model Context Protocol (MCP) tools. This provides tight integration with the Google ecosystem while allowing flexibility for external integrations.
The framework emphasizes code-first development, letting developers define agent logic, tools, and orchestration directly in Python. This approach offers ultimate flexibility, testability, and version control—treating AI agent development more like traditional software engineering than prompt hacking.
For those who prefer not to write code, Google included an Agent Config feature that allows building agents through configuration files rather than programming. This lowers the barrier to entry for non-developers while still leveraging ADK's powerful capabilities.
Multi-agent systems are a core design element. Developers can compose multiple specialized agents into flexible hierarchies, creating scalable applications where different agents handle different aspects of a workflow. For example, a coordinator agent might manage sub-agents for greeting users and executing specific tasks.
ADK comes with a built-in development UI for testing, evaluating, debugging, and showcasing agents. The visual interface displays agent interactions, function calls, and decision-making processes in real-time, making it easier to understand and refine agent behavior.
Deployment is straightforward. Agents can be easily containerized and deployed on Google Cloud Run, or scaled seamlessly with Vertex AI Agent Engine. Google has also released versions for Java, Go, and web environments, expanding ADK beyond Python developers.
The framework includes several recent innovations. A new Custom Service Registration feature provides a generic way to register custom service implementations for use in FastAPI servers. The Rewind capability allows rewinding a session to before a previous invocation, useful for testing and debugging.
Perhaps most intriguingly, ADK now includes an AgentEngineSandboxCodeExecutor class that supports executing agent-generated code using the Vertex AI Code Execution Sandbox API. This allows agents to write and run code dynamically in a secure, isolated environment.
Google has also integrated ADK with the Agent2Agent (A2A) protocol for remote agent-to-agent communication, enabling distributed systems where agents on different machines or services can collaborate on complex tasks.
The release cadence is roughly bi-weekly for stable versions via PyPI, though developers needing cutting-edge features can install directly from the main branch on GitHub. Google warns that the development version may contain experimental changes or bugs not present in stable releases.
With documentation, samples, and a growing community repository of contributed tools and integrations, Google is positioning ADK as a comprehensive solution for enterprise AI agent development. The framework's code-first philosophy and deployment flexibility make it particularly attractive for organizations already invested in the Google Cloud ecosystem.
Questions and Answers
What is Google's Agent Development Kit (ADK)?
ADK is an open-source Python framework for building, evaluating, and deploying AI agents. It applies software development principles to agent creation, offering code-first development, multi-agent orchestration, and deployment options on Google Cloud Run or Vertex AI Agent Engine. While optimized for Gemini models, it's model-agnostic and compatible with other frameworks.
Do I need to write code to use ADK?
Not necessarily. While ADK emphasizes code-first development in Python for maximum flexibility, it also includes an Agent Config feature that lets you build agents through configuration files without programming. This makes ADK accessible to non-developers while still offering the full power of the framework for those who want to code.
What are multi-agent systems in ADK?
ADK allows you to create hierarchies of specialized agents that work together. For example, you might have a coordinator agent that manages sub-agents for specific tasks like greeting users, searching the web, or executing commands. Each agent can have its own tools, instructions, and model, creating scalable applications where different agents handle different workflow aspects.
How do I deploy ADK agents?
ADK agents can be easily containerized and deployed on Google Cloud Run for serverless execution, or scaled with Vertex AI Agent Engine for more demanding workloads. Google has also released versions for Java, Go, and web environments, giving developers flexibility in choosing deployment targets and programming languages beyond Python.
