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Related Servers

Alternatives to cave-motion

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables 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.
      1
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      MCP 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.
      14
      4 npm
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Gives 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
    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides 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.
      14
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables 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

    A4/5.0

    Scored across 3 tools

    Disambiguation5/5

    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.

    Naming Consistency5/5

    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.

    Tool Count5/5

    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.

    Completeness5/5

    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.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues