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Google Antigravity SDK

Lets developers build stateful, tool-enabled Python AI agents that run on Google's Antigravity runtime. Includes built-in tools (file I/O, shell, image generation), a declarative policy/hook system, multimodal input, and MCP integration.

Introduction

Agentic applications are shifting from single-call LLM prompts to long-running, tool-driven workflows that need state, safety, and observability. Building those primitives (tool wiring, lifecycle hooks, policy enforcement, session persistence, and streaming) from scratch is time-consuming; the Antigravity SDK packages them into a local-first Python runtime so teams can focus on agent logic instead of runtime plumbing.

What Sets It Apart
  • Batteries-included runtime: ships with a consistent built-in toolset (file I/O, code editing, shell execution, directory search, image generation, sub-agent delegation) so many agent patterns work without custom plumbing — which means faster prototyping and fewer integration bugs.
  • Declarative safety and lifecycle hooks: a policy system and nine hook points let you observe, approve, or transform actions (inspect, decide, transform), enabling human-in-the-loop approvals and centralized safety rules rather than ad-hoc checks spread across code.
  • Multimodal + streaming-first: supports images, PDFs, audio, and streaming of both model output and intermediate "thoughts" or tool-call events, making it easier to build responsive UIs and to debug agent reasoning.
  • Extensible integrations: register Python callables as tools, connect MCP servers, load reusable agent skills, and deploy the same agent locally or remotely to Google Cloud with minimal code changes — so integrations scale from dev to production.
Who It's For and Trade-offs

Great fit if you need a programmatic, Python-first way to build agents that must orchestrate tools, maintain session state, and enforce safety policies (internal developer tools, automation, research prototyping). It reduces boilerplate for teams already using Google Cloud/Gemini or those experimenting with agentic patterns.

Look elsewhere if you only need a lightweight LLM client or a simple chat UI — the SDK includes a compiled runtime binary and a richer execution model that adds complexity and platform dependencies (install from PyPI to obtain platform-specific wheels). Also, projects that must avoid vendor ties or compiled binaries may prefer minimal, portable libraries instead.

Information

  • Websitegithub.com
  • OrganizationsGoogle LLC, Antigravity Team, AI Platform Team
  • Published date2026/04/29

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