mcp-luma-dream-machine
Related Servers
Alternatives to mcp-luma-dream-machine
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityDmaintenanceA server that provides Luma AI's video generation API as the Model Context Protocol (MCP)3-
- AlicenseAqualityBmaintenanceMCP server for the XBrush AI media generation API, enabling image, video, audio generation, editing, and more directly from Claude Code via async polling.2128MIT
- AlicenseAqualityCmaintenanceAn MCP server that enables generating images via OpenAI and images/videos via Google Gemini (including Veo video generation), saving outputs to local asset folders. It integrates with Claude Code and any MCP client using your own API keys.3MIT
- AlicenseBqualityDmaintenanceMCP server for generating and editing images using OpenAI, and creating videos using OpenAI Sora and Google Veo. Enables fetching media from URLs or disk with smart output placement.14179MIT
- AlicenseAqualityBmaintenanceMCP server for AI-powered image, audio, and video generation, enabling media creation directly from Claude, Cursor, and other MCP clients.1164MIT
- FlicenseBqualityDmaintenanceA production-ready MCP server that enables Claude and other LLMs to generate images and videos using Google's Gemini AI models (Gemini 2.0 Flash and Veo 2.0).32-
TDQS
Scored across 10 tools
Most tools have distinct purposes, but there is some potential overlap between 'create_generation' (for video from text/image/video) and 'generate_image' (for image from text), which could cause confusion about when to use each. Otherwise, tools like 'add_audio', 'upscale_generation', and 'get_camera_motions' are clearly differentiated.
All tools follow a consistent verb_noun pattern with snake_case, such as 'create_generation', 'delete_generation', 'get_camera_motions', and 'upscale_generation'. The naming is predictable and uniform across the set.
With 10 tools, the count is well-scoped for a video/image generation API. It covers core operations like creation, retrieval, listing, deletion, and enhancement, without being overwhelming or too sparse.
The toolset provides good coverage for video and image generation workflows, including CRUD operations for generations and additional features like audio addition and upscaling. A minor gap is the lack of tools for modifying existing generations (e.g., update or edit), but agents can work around this by recreating or upscaling.