mlx-serve-mcp
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- FlicenseNot gradedqualityCmaintenanceEnables AI clients like Claude and ChatGPT to generate images and videos, animate images, create lip-synced videos, list TTS voices, and manage media via remote MCP tools.-
- AlicenseNot gradedqualityAmaintenanceEnables MCP-compatible clients to generate images and videos, synthesize text-to-speech audio, and clone or design custom voices. It also supports flexible output handling (URLs or local files) and multiple transport modes including stdio, REST, and SSE.549 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables MCP-compatible clients such as Claude Desktop and Cursor to generate images and videos, synthesize speech, clone voices, and design custom voices from descriptive prompts. It supports stdio, REST, and SSE transport modes with configurable API hosts, keys, and local or URL-based resource output.549 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables MCP-compatible clients to generate images and videos, synthesize speech, clone voices, and design custom voices through MiniMax APIs, with configurable transport modes and resource output.549 npmMIT
- AlicenseAqualityCmaintenanceMCP server for AI-powered image, audio, and video generation, enabling media creation directly from Claude, Cursor, and other MCP clients.1143 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables users to generate images and videos, synthesize speech, clone voices, and design custom voices through MiniMax APIs from MCP-compatible clients.549 npmMIT
TDQS
Scored across 10 tools
Each tool targets a distinct modality or administrative action: TTS, music, video, 3D, image generation, image editing, health check, and model management. No two tools overlap in purpose, and even the two audio tools are clearly separated by speech vs. music.
The set mostly follows a verb_noun pattern: generate_music, generate_video, generate_image, edit_image, list_models, load_model, unload_model. text_to_speech breaks the pattern slightly, but it is still readable and the deviation is minor.
Ten tools is well-scoped for a media-generation server: creative generation/edit tools, TTS, and operational tools for health and model management. Each tool earns its place and none feel redundant.
Core media generation workflows are well covered: image generation/edit, video, music, TTS, and 3D mesh generation, plus model lifecycle management. The main gap is that list_models advertises chat/vision capability, but no chat or vision tool is exposed, leaving that part of mlx-serve unreachable.