Overview
Compare OpenAI official Agents SDK and Google official Agent Development Kit across protocol, model support, tool calling, and deployment model.
Python · MIT
OpenAI Agents SDK is OpenAI's official agent development toolkit, supporting the building of multi-step workflow AI agents with core features like tool calling and state management.
Python · Apache-2.0
Google Agent Development Kit (ADK) is Google's agent development framework for building complex AI agent systems with tool integration and multimodal processing capabilities.
| Best for | OpenAI Agents SDK | Agent Development Kit |
|---|---|---|
| Core positioning | OpenAI official lightweight Python/JS SDK focused on multi-agent handoffs, tool calling, tracing, and Realtime API with deep OpenAI model integration | Google official full-stack Agent development framework covering Python/Java/Go, emphasizing Gemini model and Google Cloud ecosystem integration |
| Best for | Small-medium projects using OpenAI models, needing Realtime voice agents, and multi-agent handoff workflows | Medium-large enterprise Agent applications using Gemini models, needing multi-language support and Google Cloud integration |
| Multi-agent collaboration | Built-in Handoffs primitive, agents transfer control via message handoffs, model automatically decides handoff timing | Built-in SubAgent and SequentialAgent components, supports LLM-driven and workflow two orchestration modes |
| Deployment and ecosystem | Local Python/JS process or container deployment, native integration with OpenAI suite (Realtime, TTS, Whisper) | Supports local, Vertex AI Agent Engine, Cloud Run multiple deployment modes, deep integration with Google Cloud services |
| Metric | OpenAI Agents SDK | Agent Development Kit |
|---|---|---|
| Stars | 15.0k | 20.8k |
| Forks | 1.2k | 3.7k |
| Language | Python | Python |
| License | MIT | Apache-2.0 |
| Last commit | March 5, 2026 | July 20, 2026 |
Choose based on your primary workflow, language ecosystem, and integration needs. Review each project's documentation and recent GitHub activity before adopting it in production.