google-adk

Google's ADK enables multi-agent system design in Python through LlmAgent, SequentialAgent, ParallelAgent, and LoopAgent patterns. You orchestrate agents, integrate tools, manage memory and state, and deploy production workflows with built-in observability and error handling.

The ADK supports sequential, parallel, and loop workflow patterns for orchestrating multi-agent systems. These patterns enable flexible agent coordination, from linear task chains to concurrent execution and iterative loops with custom tool integration.

Yes, the ADK provides production deployment patterns, performance evaluation, observability, and robust error handling. It supports memory management strategies, human-in-the-loop workflows, and OpenAPI and MCP integrations for production-ready agent systems.

The ADK enables custom tool creation within a built-in and extensible tool ecosystem. You design memory and state management strategies tailored to your agent's workflow, integrating OpenAPI endpoints and MCP protocols for dynamic tool access and persistent state.

Start with a simple LlmAgent prototype—such as a weather assistant—using a custom tool. The ADK's code-first approach lets you define agent behavior, bind tools, and test end-to-end workflows without boilerplate setup.

Yes, the ADK integrates OpenAPI and MCP protocols natively, enabling agents to consume external APIs and services. This supports dynamic tool binding, flexible orchestration, and interoperability with standard agent communication frameworks.