The NVIDIA Omniverse GitHub organization hosts the standalone Omniverse libraries, OpenUSD tooling and SDKs, and sample code repositories that demonstrate the use of Omniverse technologies.
Standalone, embeddable libraries that bring core Omniverse technologies to any application. Each provides C and/or Python APIs, and most ship agent skills for AI-assisted development (see Agent Skills and MCP Servers below).
| Library | Description |
|---|---|
| ovrtx | A C and Python library for physically accurate, real-time sensor simulation and visualization using NVIDIA Omniverse RTX. |
| ovphysx | USD physics simulation built on the NVIDIA PhysX SDK — C API with Python bindings, DLPack tensor interop, and environment cloning for batched reinforcement learning. Part of the PhysX repository. |
| ovui | The standalone distribution of Omniverse's omni.ui UI framework — a declarative, Python-first API for building hardware-accelerated desktop interfaces backed by ImGui — plus application widget and OpenUSD data-adapter layers. |
| ovstream | C library with Python bindings for streaming video, audio, and input over WebRTC, RTSP, native (StreamSDK), and SHM (shared-memory) transports, with GPU-accelerated NVENC encoding. |
| ovstorage | Agent-first, plugin-based storage client for local files, cloud object stores, and Omniverse Storage services. |
| ovpackage | Command-line tool and async Python API for reproducible asset packaging and publishing across local and cloud storage backends. |
Libraries and services for authoring, validating, converting, optimizing, and searching OpenUSD content:
- usd-exchange — OpenUSD Exchange SDK for authoring consistent and correct USD (samples)
- usd-validation-nvidia — extensible framework to validate OpenUSD assets
- usd-profiles-nvidia — framework for defining and managing OpenUSD asset profiles, capabilities, and requirements
- usd-optimize — library to optimize OpenUSD stages
- usd-convert-asset, usd-convert-cad, and usd-convert-gsplat — converters for common asset formats, CAD data, and 3D Gaussian Splats
- usd-search — cloud-native microservices for searching OpenUSD asset collections by natural language or reference image (client library)
- omniverse-labs — experimental Omniverse projects, including the nanousd family of lightweight USD tools
Agent Skills and MCP (Model Context Protocol) servers help AI coding assistants work with Omniverse technologies. Skills provide structured reference docs that agents can load on demand, and MCP servers expose searchable tool APIs for Kit extensions, USD, and OmniUI.
| Name | Type | Description | Repository |
|---|---|---|---|
| ovrtx | Agent Skills | Omniverse RTX SDK — renderer setup, USD scene loading, rendering, attribute writing, CUDA/Vulkan interop, and project scaffolding. | ovrtx/skills/ |
| ovphysx | Agent Skills | USD physics simulation — C API with Python bindings, DLPack tensor interop, environment cloning for batched RL, and rigid body simulation. | PhysX/ovphysx/ |
| ovui | Agent Skills | Standalone omni.ui framework — declarative Python UI building, widgets, layout, and styling. | ovui/skills/ |
| ovstream | Agent Skills | Streaming library — video, audio, and input streaming over WebRTC, RTSP, native, and shared-memory transports. | ovstream/skills/ |
| ovstorage | Agent Skills | Storage client — local files, cloud object stores, and Omniverse Storage services. | ovstorage/skills/ |
| ovpackage | Agent Skills | Asset packaging and publishing — CLI and Python API workflows. | ovpackage/.agents/skills/ |
| Kit MCP | MCP Server | Kit development assistant — semantic search across 400+ extensions, dependency graphs, API docs, code examples, and app templates. | kit-usd-agents/source/mcp/kit_mcp/ |
| USD Code MCP | MCP Server | USD/OpenUSD development assistant — module and class browsing, method signatures, code examples, and semantic search. | kit-usd-agents/source/mcp/usd_code_mcp/ |
| OmniUI MCP | MCP Server | OmniUI development assistant — class and module browsing, method docs, code examples, and system instructions. | kit-usd-agents/source/mcp/omni_ui_mcp/ |
The following NVIDIA Physical AI skills are available:
- omniverse-cad-to-simready
- omniverse-realtime-viewer
- omniverse-usd-performance-tuning
- physical-ai-defect-image-generation
- physical-ai-infrastructure-setup-and-resilient-scaling
- physical-ai-neural-reconstruction
- physical-ai-video-data-augmentation
These skills are also available in Vercel's Skill Marketplace under the Physical AI section, and as plugins in the Claude Code marketplace and Codex marketplace.
See also the NVIDIA Agent Skills catalog for skills across the NVIDIA ecosystem.
Omniverse Workflows and Blueprints provide step-by-step guides and reference implementations for a variety of development scenarios. They can help you get started quickly with use cases such as virtual facility integration (VFI), configurator development, synthetic data generation, and more. These resources build on repositories in this Omniverse GitHub organization.
