@retomagic/mcp
OfficialRelated Servers
Alternatives to @retomagic/mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityCmaintenanceEnables video and image generation from any MCP client, with support for models like Veo 3.1, Grok Imagine, and Nano Banana, including text-to-video, image-to-video, image generation and editing.4MIT
- AlicenseAqualityBmaintenanceEnables generating and editing images and videos from any MCP client using SayMaker's model lineup, with credit cost reporting and async task polling.649 npmMIT
- AlicenseAqualityAmaintenanceEnables AI image and video generation using Midjourney through the AceDataCloud API. It supports comprehensive features including image creation, transformation, blending, editing, and video generation directly within MCP-compatible clients.164,844 PyPI11MIT
- AlicenseAqualityBmaintenanceImage tools for coding agents: generate from text, edit one reference image, remove backgrounds, upscale 2x, and create reference-based sprite animations. The MCP server, CLI and REST API share one key, credit balance and request history. Needs a DreamLayer API key and paid credits; sprite sheets are beta.7277 npmMIT
- AlicenseAqualityCmaintenanceEnables image and video generation through the SimpleNGAT API, including text/image-to-video, voice-driven video, image upscaling, and health checks, from MCP-compatible clients.8MIT
- 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.41412 npm9MIT
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: generating content, checking prediction status, and listing available models. There is no overlap or ambiguity.
All tool names follow a consistent verb_noun pattern with lowercase and underscores (generate, get_prediction, list_models), making them predictable and easy to understand.
Three tools is appropriate for the server's scope: model discovery, content generation, and result retrieval. Each tool serves a necessary function without excess or deficiency.
The tool surface covers the full workflow: listing models to know available options, generating content with optional polling, and checking results asynchronously. No obvious gaps for the intended purpose.