cave-motion
Related Servers
Alternatives to cave-motion
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables AI coding agents to search and fetch tested, version-pinned, multi-library code recipes complete with files, setup and test commands, and receipts proving they currently pass. Recipes are re-tested on upstream releases, so agents only receive implementations that are up to date and verified.1MIT
- AlicenseAqualityCmaintenanceMCP server over a catalog of production-grade GSAP and WebGL motion components. Your agent can plan a page's sections, pick a mechanic for each one, get composition rules so animations don't fight each other, and fetch build prompts validated against live demos. Hosted at motionprompts.dev/mcp or local with npx motionprompts-mcp.144 npm-

Duchampofficial
AlicenseNot gradedqualityBmaintenanceGives coding agents a curated, reviewable library of landing pages, hero sections, image prompts, motion-video recipes, logo and pitch-deck recipes, fonts and motion backgrounds that they can search, inspect and fetch, then rebuild locally from code. Searches and reference inspection are uncounted, while template, UI and asset fetches share a daily free limit under OAuth sign-in with no API key.MIT- AlicenseNot gradedqualityBmaintenanceEnables searching, inspecting, auditing, and composing AI video prompts using 150 verified prompts that were each rendered into real Seedance 2 videos.23 npmMIT
- AlicenseNot gradedqualityDmaintenanceProvides AI assistants with comprehensive access to Motion.dev animation library documentation and code generation tools. Enables LLMs to generate Motion animations for React, JavaScript, and Vue with proper documentation backing and framework conversion capabilities.14MIT
- AlicenseNot gradedqualityCmaintenanceEnables LLM agents to generate and validate multi-granularity storyboard assets from text prompts, including 2D SVG motion, 3D Blender depth/blockout, and SDXL ControlNet final images. It also supports vision-based self-correction and a SQLite knowledge database of successful recipes.MIT
TDQS
Scored across 3 tools
Each tool targets a distinct stage: search finds recipes, get reads recipe details, and prepare builds a prompt. Their descriptions explicitly clarify boundaries and handoffs.
All three tools follow the same verb_motion pattern: search_motion, get_motion, prepare_motion. The shared noun and consistent verb-first style make the set predictable.
Three tools are well-scoped for a focused recipe-discovery-and-preparation workflow. Each tool has a clear role in the sequence, with no unnecessary surface area.
The surface covers the full expected lifecycle: discover recipes, inspect recipe details including dependencies and licensing, then prepare a motion prompt. No obvious dead ends for the stated purpose.