kinetograph: A blazingly fast programmatic video engine, made for agents

by 0xS4N4TG · MCP Server · ★ 86

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install kinetograph

npx kinetograph still examples/rajz-cards/index.tsx 60 -o out/rajz-60.png
npx kinetograph strip examples/rajz-cards/index.tsx -n 12 -o out/rajz-strip.png

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 58/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentsai-agentsffmpeggpumcpmotion-graphicsprogrammatic-videoreactremotionrust

Quick Facts

Stars86
Forks11
LanguageTypeScript
CategoryMCP Server
Quality Score58/100
Open Issues5
Last Updated2026-10-26
Created2026-10-23
Platformsmcp, node
Est. Tokens~16k

About kinetograph

kinetograph. A blazingly fast programmatic video engine, made for agents. Examples · Editor · Get started · The engine · Use with agents You (or an agent) write a video in TypeScript with Remotion's API, CSS, SVG, Canvas 2D, WebGL shaders and Web Audio; Node runs the code; a Rust GPU compositor, loaded into Node as an N-API addon, draws every frame.

Compatible Skills

These tools work well together with kinetograph for enhanced workflows:

kinetograph alternative? Top 6 similar tools

Looking for a kinetograph alternative? If you're comparing kinetograph with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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