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AI models shouldn't guess coordinates. FastSVG computes them.

Geometry, color, motion and APNG — solved with math, exposed over MCP.

tests runtime deps node license

 

Install

git clone https://github.com/Syron01/fastsvg && cd fastsvg
npm install && npm test
npx tsx apps/cli/src/main.ts render scene.json --out out.png    # scene → PNG
npx tsx apps/cli/src/main.ts compare a.png b.png                # pixel diff

Related MCP server: svg-mcp

Use with your model

{ "mcpServers": { "fastsvg": { "command": "npx", "args": ["fastsvg-mcp"] } } }

"Animate the box 20px right, ease-in-out, export a 10fps APNG."

Ten tools: create_scene · apply_patch · build_path · create_gradient · render_png · export_apng · compare_images · …

What's inside

scene-ir

typed scene model, atomic patches

geometry

exact Bézier bounds, arc length, reverse

color-engine

sRGB ↔ linear ↔ OKLab, WCAG contrast

gradient-engine

perceptual stops, ΔE banding report

motion-engine

keyframes, cubic-bezier, damped springs, loop-seam check

raster

alpha blending, 2×2 anti-aliased fills

apng-exporter

PNG/APNG codec written from scratch

frame-pipeline

scene + timeline → deterministic APNG

vision

pixel diff, changed-region bbox, silhouette IoU

Limits

Boolean ops, gradient raster fills and delta-frame APNG aren't implemented yet. Everything shipped is tested — full spec · live demo.

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