SVG to Video

io.github.GehDocPublished by GitHub account GehDocv0.34.0Updated Nov 11, 2026

Convert animated SVG (CSS/SMIL) to video (MP4/WebM) or image (GIF/aPNG) with in-band delivery.

VerifiedSTDIODesktop onlyDeveloper ToolsMedia & Design

Overview

AI-generated overview

Converts CSS- and SMIL-animated SVG files into MP4, WebM, MKV, MOV video or aPNG/GIF images, with optional transparency, for an AI assistant.

What you can do
  • Render animated SVG files into video or animated image formats
  • Set resolution, duration, frame rate, output format and transparent background
  • Attach custom titles and comments as metadata to the output
  • Return the converted result in-band to the assistant
When to use it
Useful when you have animated SVG assets and want an assistant to turn them into shareable video or GIF/aPNG files, for example for documentation, chat previews, overlays or CI-generated demos.
Requirements
Runs locally over stdio via npx (Node.js) or the Docker image; the CLI path needs Node.js and FFmpeg installed. Docker needs a larger shared memory setting for Chromium rendering. No authentication is declared. Optional environment variables: DO_NOT_TRACK, MCP_HOSTED, PUPPETEER_ARGS, PUPPETEER_EXECUTABLE_PATH.
Before you install
Anonymous usage telemetry is sent by default (conversion counts and format usage, no SVG contents); set DO_NOT_TRACK to opt out. The server reads local SVG files and writes output files, so point it only at directories you intend to expose. MCP_HOSTED can forbid local file path arguments for sandboxing. Puppeteer flags and a custom Chromium path are passed through to the browser process.

Installation

In SourceWeft

  1. Open SVG to Video in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

SVG to Video

[CI] [Last Commit] [GitHub Release] [npm Version] [Docker Image] [MCP Registry] [HuggingFace Space] [llms.txt]

A high-fidelity tool to transform your CSS- and SMIL-animated SVGs into high-quality videos (MP4, WebM, MKV, MOV) or lightweight animated formats (aPNG, GIF) with perfect alpha-channel transparency directly in your browser or via CLI/MCP server.

[SVG to Video Demo]

Automated demo generated by our CI/CD pipeline


🌟 Why SVG to Video?

  • Transparent Backgrounds: Export your animations with a full alpha channel using WebM or aPNG, and optimized indexed transparency with GIF89a. Perfect for overlays in video editing tools or web use.
  • Privacy-First: The Web Studio runs entirely in your browser—your SVG files never leave your computer.
  • Frame-Accurate: Our engine scrubs both the Web Animations API and native SVG SMIL, ensuring every frame is captured exactly as rendered.
  • AI Agent Native: Native Model Context Protocol (MCP) server and Agent Skill (SKILL.md) support indexed on the official MCP Registry (mcp.json) and hosted live on HuggingFace Spaces.
  • Universal Animated Formats: Beyond video, generate lightweight Animated PNGs (aPNG) and GIFs perfect for documentation, Slack, or GitHub, with full control over background transparency.
  • Copy to Clipboard: Instant export to Base64 Data URL—copy your video and embed it directly into your HTML, CSS, or JS code without manual downloads. Perfect for rapid prototyping and developers.
  • Metadata Injection: Support for custom titles and comments across video (MP4, WebM, MKV, MOV) and animated image (aPNG, GIF) formats.
  • Versatile: Whether you need an accessible Web Studio for quick conversions or a powerful CLI tool for batch automation and CI/CD pipelines, this project has you covered.

🚀 Getting Started

Choose the entry point that matches your needs:

  • Web Studio: The easiest way to convert SVGs to video, high-fidelity aPNG, or optimized GIF in your browser without any installation.
  • CLI / Docker Tool: For batch processing, server-side automation, and CI/CD integration.
  • AI Agent & MCP Server: For Claude Desktop, Cursor, Antigravity, and autonomous LLM workflows.

🌐 Web Studio

🚀 Try the Web Studio

Our Web Studio is a serverless, client-side rendering tool. It runs entirely in your browser using WebCodecs—your SVG files never leave your computer, ensuring absolute privacy. The interface is optimized for high-productivity on screens starting from 720p resolution.

Automated Demo: The demo video at the top of this README is automatically generated and updated by our CI/CD pipeline using Playwright and Driver.js, ensuring it always reflects the latest UI changes.

Privacy Note: We use Umami Analytics to collect anonymous usage data across our Web Studio, CLI, and MCP server interfaces (e.g., number of conversions and format usage) to help us improve the tool. This tracking is cookie-less, respects standard "Do Not Track" settings (set the DO_NOT_TRACK=1 environment variable to opt out), and never collects personal information or SVG contents. See docs/ANALYTICS.md for details.

Explore our Visual Gallery (Storybook) to see how the engine handles complex CSS, SMIL, and fonts.

Quick Start

  1. Open the Web Studio.
  2. Drag and drop your .svg file, or test the engine instantly with 1-click built-in samples.
  3. Adjust resolution, duration, and FPS.
  4. Select your format, toggle Transparent Background if needed, and ensure High-Fidelity Capture is enabled for best results.
  5. Click Export.

🚀 CLI / Docker Tool

For automated or batch processing, use the CLI tool. It is built to run in a headless environment, making it perfect for CI/CD pipelines or server-side automation.

Quick Start

Ensure Node.js and FFmpeg are installed.

bash
# Node.js (auto-detected duration)npx -y -p @gehdoc/svg-to-video svg-to-video input.svg 60 ./out-dir
# Node.js (explicit duration & GIF output)npx -y -p @gehdoc/svg-to-video svg-to-video input.svg 60 ./out-dir -d 5 --format gif --transparent
# Node.js (custom resolution dimensions e.g. vertical 1080x1920)npx -y -p @gehdoc/svg-to-video svg-to-video input.svg 60 ./out-dir --resolution 1080x1920
# Node.js (animated PNG output)npx -y -p @gehdoc/svg-to-video svg-to-video input.svg 60 ./out-dir -d 5 --format apng
# Docker (zero local dependencies; requires --shm-size=2gb for Chromium rendering; add :Z to -v for SELinux / Fedora)docker run --rm --shm-size=2gb -e PUPPETEER_ARGS="--no-sandbox" -v $(pwd):/data:Z gehdoc/svg-to-video /data/input.svg 60 /data/out-dir -d 5 --format gif

See docs/CLI.md for full usage, arguments, and options. For local building and source execution, see CONTRIBUTING.md.


🤖 AI Agent & MCP Integration

Connect svg-to-video to AI Assistants (Claude Desktop, Cursor, Antigravity, AutoGPT) via Model Context Protocol:

  1. Add to mcpServers config:
    json
    {  "mcpServers": {    "svg-to-video": {      "command": "npx",      "args": ["-y", "-p", "@gehdoc/svg-to-video", "svg-to-video-mcp"]    }  }}
  2. Prompt your AI Assistant:

    "Convert examples/example.svg into a 60fps transparent WebM video."

See docs/MCP.md for full setup instructions, tool schemas, Docker execution, and agent prompting guides.


🔗 Official Package Distributions


📦 Quick Installation & Execution

bash
# Run on-demand via npx (no global installation required)npx -y -p @gehdoc/svg-to-video svg-to-video input.svg 60 ./out-dir
# Install globally via npmnpm install -g @gehdoc/svg-to-video
# Pull official Docker image from Docker Hubdocker pull gehdoc/svg-to-video:latest

🛠 Technical Details

For a deep dive into the rendering engine, algorithms, and infrastructure, see docs/ARCHITECTURE.md.

The tool works by isolating the SVG, scrubbing both the Web Animations API and native SVG SMIL DOM, and capturing frames via WebCodecs or FFmpeg.


❓ FAQ

Common questions about privacy, how frame scrubbing works, CI/CD automation, and transparency support are answered in docs/FAQ.md.


🤝 Contributing

Contributions are welcome! This project follows a Spec-Driven Development (SDD) workflow to ensure clear requirements and high quality. Please open an issue or pull request.

Check out our Active Roadmap to see what we're working on next.

For instructions on contributing, build commands, security standards, and the technical roadmap, please see CONTRIBUTING.md.


💖 Support the Project

If you find this tool helpful, please consider supporting its development:

[Donate]

Your support helps cover maintenance and further development of the tool. Thank you!


📜 License

This project is licensed under the MIT License.

Source: README.md at commit 1ef6b94

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

17
  1. v0.34.0LatestNov 11, 2026
  2. v0.33.0Oct 19, 2026
  3. v0.32.1Oct 19, 2026
  4. v0.31.0Oct 18, 2026
  5. v0.30.0Oct 14, 2026
  6. v0.29.5Oct 13, 2026
  7. v0.29.4Oct 13, 2026
  8. v0.29.3Oct 8, 2026
  9. v0.29.2Oct 7, 2026
  10. v0.29.0Oct 6, 2026
  11. v0.28.4Oct 5, 2026
  12. v0.28.3Oct 3, 2026
  13. v0.28.2Oct 3, 2026
  14. v0.27.8Sep 29, 2026
  15. v0.27.6Sep 28, 2026
  16. v0.27.5Sep 27, 2026
  17. v0.27.3Sep 26, 2026

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  • Reached in the last 30 days25 pts

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  • Auth declared10 pts

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  • Tools listed15 pts

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