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With AI, Everyone is a Dev. EveryDev.ai © 2026
    1. Home
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    3. vgpu
    vgpu icon

    vgpu

    AI Development Libraries

    A modular TypeScript WebGPU library for building cross-runtime shader applications in browsers, headless Node.js, and CI pipelines, designed for both developers and coding agents.

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    At a Glance

    Pricing
    Open Source

    Free and open-source under the MIT License. Install via npm and use without restriction.

    Engagement

    Available On

    Web
    CLI
    API
    SDK

    Resources

    WebsiteDocsGitHubllms.txt

    Topics

    AI Development LibrariesAgent Skill Registries3D and Animation

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    TanStack IntentRemotionCADAM
    Developer
    Vercel LabsSan Francisco, CAEst. 2015$863M raised

    Listed Sep 2026

    About vgpu

    vgpu is an open-source TypeScript library for WebGPU maintained by Vercel under the MIT License. It lets developers write modular WGSL shaders once and run them across interactive browser canvases, headless Node.js rendering, image and video export, and automated CI test suites — all through a single composable API. The project is developed in the open at vercel-labs/vgpu on GitHub and published as the vgpu package on npm.

    What It Is

    vgpu is a cross-runtime WebGPU rendering library that treats WGSL shader files like TypeScript modules. Its core job is to eliminate the friction of writing GPU code that works in multiple environments: the same shader compiles and runs in a browser canvas, a headless Dawn-backed Node.js process, and a deterministic mock adapter for unit tests. The library resolves WGSL import graphs at build time, reflects binding names and layouts automatically, prunes unused declarations, and emits compact shader source — a complete fullscreen effect ships in 25 KB gzipped, a budget enforced in CI.

    Architecture and Package Structure

    vgpu is a monorepo with a layered package design:

    • vgpu — the public main API: init, draw, compute, effect, frame, bundle, target, uniforms, plus scene and core subpaths.
    • @vgpu/cli — the vgpu command-line binary for docs, shader validation (check), and runtime diagnostics (doctor).
    • @vgpu/core — low-level WebGPU wrappers (Device, Buffer, Texture, bind groups).
    • @vgpu/wgsl — turns .wgsl files into JS modules and resolves WGSL-to-WGSL imports before bundling.
    • @vgpu/wgsl-std — standard WGSL utility modules (math, color, sampling, noise, hash).
    • @vgpu/adapter-node — Dawn-backed adapter used by vgpu/node.
    • @vgpu/adapter-mock — deterministic mock adapter used by vgpu/mock for tests and CI.

    The single Gpu context returned by init() is passed explicitly to every entry point — there is no hidden global state.

    Agent-Ready Design

    vgpu is explicitly built to be operated by coding agents as well as human developers. The CLI exposes docs, examples, WGSL validation, and runtime diagnostics so agents can access them without a browser:

    • npx vgpu docs — read the API reference from the terminal
    • npx vgpu examples — search and pull reference examples locally
    • npx vgpu check — validate WGSL shader source
    • npx vgpu doctor — diagnose the runtime environment

    The project publishes agents.md, llms.txt, and llms-full.txt at vgpu.sh for LLM consumption, and exposes a tokenless read-only Examples discovery API described by an OpenAPI 3.1 spec. An MCP endpoint at https://vgpu.sh/api/mcp connects agents to documentation and verified examples, and a local stdio MCP server can be run with npx vgpu mcp for package-versioned offline access. vgpu is also listed in the Vercel Agent Stack alongside AI SDK, AI Gateway, Sandbox, and Workflows.

    Multi-Runtime Rendering Workflow

    The library's rendering model is explicit rather than scene-graph-based. frame(gpu, (f) => f.pass(target, effect)) makes passes, clears, and draws explicit calls. Targets can be a browser canvas surface, a headless RGBA texture, an image file, or a video output. The same shader code path runs across all of them. For CI, vgpu renders a headless frame, compares a snapshot, and reports pass/fail — enabling GPU rendering tests in automated pipelines without a display.

    Update: v0.3.1

    The latest release is v0.3.1, published on 2026-08-26. The repository was created in May 2026 and has seen active development, with the last push on 2026-08-28. The project has accumulated 823 stars and 31 forks on GitHub. Product direction signals continued investment in agent tooling, MCP integration, and cross-runtime rendering parity.

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    Pricing

    OPEN SOURCE

    Open Source

    Free and open-source under the MIT License. Install via npm and use without restriction.

    • Full vgpu TypeScript library
    • Browser and headless Node.js rendering
    • Typed WGSL shader imports
    • CLI for docs, examples, and validation
    • MCP server integration

    Capabilities

    Key Features

    • Typed WGSL shader imports like TypeScript modules
    • Single Gpu context with no hidden global state
    • Cross-runtime: browser, headless Node.js (Dawn), and mock adapter
    • Automatic WGSL binding reflection — no manual declarations
    • Build-time import graph resolution and dead-code pruning
    • Explicit frame/pass rendering model
    • CLI for docs, examples, WGSL validation, and runtime diagnostics
    • MCP endpoint for agent integration
    • llms.txt and agents.md for LLM consumption
    • Headless rendering for images, video, and CI snapshots
    • Standard WGSL utility library (math, color, noise, hash)
    • 25 KB gzipped budget enforced in CI
    • OpenAPI 3.1 Examples discovery API
    • Deterministic mock adapter for unit tests

    Integrations

    WebGPU
    Node.js
    Dawn (WebGPU native backend)
    ONNX Runtime Web
    Vercel AI SDK
    Vercel AI Gateway
    Vercel Sandbox
    Vercel Workflows
    MCP (Model Context Protocol)
    npm
    TypeScript
    Next.js
    CI/CD pipelines
    API Available
    View Docs

    Ratings & Reviews

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    Developer

    Vercel Labs

    Vercel Labs builds experimental open-source projects under the Vercel umbrella, exploring new paradigms in developer tooling and AI-assisted programming. The team behind Zerolang focuses on graph-native language design to tighten the loop between AI agents and compilers. Vercel Labs releases projects under permissive open-source licenses, inviting community contribution and iteration.

    Founded 2015
    San Francisco, CA
    $863M raised
    600 employees

    Used by

    Shopify
    Zapier
    Notion
    Mintlify
    +5 more
    Read more about Vercel Labs
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