Agent Development Kit - Google's open-source AI Agent development and deployment framework

What is Agent Development Kit

Agent Development Kit (ADK) is Google's first open-source AI agent development toolkit. It is a code-first Python toolkit that simplifies the process of building, evaluating, and deploying complex AI agents. ADK supports multi-agent architectures and can build hierarchical applications composed of multiple specialized agents, enabling complex coordination and delegation. It provides a rich tool ecosystem, including pre-built tools, custom functions, and third-party library integrations. Through built-in workflow agents and LLM-driven dynamic routing, ADK can flexibly define complex workflows. It provides integrated development tools, native streaming support, built-in evaluation tools, and broad LLM support. The open-sourcing of ADK lowers the barrier to AI agent development, allowing developers to build fully functional AI agents in fewer than 100 lines of code, with high flexibility and strong compatibility, supporting multiple LLM models.

Main features of Agent Development Kit

• Multi-agent architecture: ADK supports building hierarchical applications composed of multiple specialized agents, enabling complex coordination and delegation. Developers can define agents at different levels, with each agent focusing on a specific task, improving the overall efficiency and scalability of the system.
• Rich tool ecosystem: ADK provides pre-built tools (such as search and code execution), custom functions, and third-party library integrations. Developers can easily extend agent capabilities to meet diverse needs.
• Flexible orchestration: ADK includes multiple built-in workflow agents (such asSequentialAgent、ParallelAgent、LoopAgent), supports LLM-driven dynamic routing, and can flexibly define complex workflows to meet task requirements in different scenarios.
• Integrated development tools: ADK provides a command-line interface (CLI) and developer UI, supporting running agents, inspecting execution steps, debugging interactions, and visualizing agent definitions. It helps developers quickly develop, debug, and optimize agents.
• Native streaming support: ADK supports bidirectional streaming interaction (text and audio) and integrates seamlessly with underlying capabilities (such as the Gemini Developer API). This enables agents to respond to user input in real time and provides a smoother interaction experience.
• Built-in evaluation tools: ADK provides tools for systematically evaluating agent performance, including evaluation of final response quality and step-by-step execution traces. This helps developers optimize agent performance and ensure its reliability in real-world applications.
• Broad LLM support: Although ADK is deeply integrated with Google's Gemini models, through theBaseLlminterface, it also supports integration with various LLMs (such as Anthropic, Meta, Mistral AI, etc.). This provides developers with more choices and flexibility.
• Rapid deployment: ADK supports a seamless transition from local development to cloud deployment. Developers can iterate quickly locally and migrate to the cloud for large-scale deployment.
• Code-first development approach: ADK adopts a code-first development approach, directly defining agent behavior, orchestration logic, and tool usage through Python code. It provides maximum control, testability, and version control, enabling developers to leverage existing software development best practices.

Agent Development Kit project address

• Github repository：https://github.com/google/adk-python
• Project documentation：https://google.github.io/adk-docs/

Application scenarios of Agent Development Kit

• Customer service assistants and business process bots: ADK is very well suited for rapidly developing customer service assistants and business process bots. Developers can use a multi-agent architecture and a rich tool ecosystem to build agents that can handle a variety of tasks.
• Multi-Agent Collaboration Systems: ADK's multi-agent architecture supports developers in building complex collaborative systems. For example, a weather query system can include a main agent (such asWeatherAgent), delegate greeting tasks to a dedicated greeting agent (such asGreetingAgent), and delegate farewell tasks to a farewell agent (such asFarewellAgent), while focusing itself on handling weather queries.
• Enterprise Internal Tool Integration: ADK supports integration with a variety of external APIs and tools, making it possible to build a "multi-AI toolbox" for internal teams.
• Interaction Between Agents: ADK supports the Agent2Agent protocol (A2A), enabling agents to exchange information based on a standard protocol.