dsh-image-generate
Related Servers
Alternatives to dsh-image-generate
No user-submitted related servers found.
Related Servers
- AlicenseAqualityCmaintenanceMCP server for generating images and videos using Volcengine's Jimeng APIs, supporting text-to-image, image-to-image, multi-image fusion, text-to-video, and image-to-video.31MIT
- AlicenseAqualityBmaintenanceMCP server for recognizing and generating images, videos, and audio via DashScope, with support for large video uploads and local output previews.7MIT
- FlicenseAqualityDmaintenanceMCP server for AI image generation supporting text-to-image and image-to-image editing via any OpenAI-compatible service, with configurable models, aspect ratios, and sizes.2-
- AlicenseNot gradedqualityCmaintenanceMCP server for generating, editing, and processing images via multiple providers including Kilo, OpenRouter, OpenAI, and Gemini, with local tools for background removal, resizing, and cropping.19 npm3MIT
- FlicenseNot gradedqualityDmaintenanceAn MCP server for generating images and videos via external multimodal models, providing unified tools like imageGenerate, videoGenerate, and materialWrite with support for normal and smart generation modes.-
- 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 5 tools
Each tool targets a distinct operation: text-to-image, image editing, model listing, video generation, and status query. The overlapping media types are clearly differentiated by purpose and parameters, leaving no ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case (generate_image, edit_image, list_models, generate_video, get_video_status). The style is uniform and predictable across the set.
With 5 tools covering image and video generation plus supporting operations, the count is well-scoped for the server's purpose. Each tool earns its place without redundancy or bloat.
The core workflows are covered: text-to-image, image editing, text/video-to-video, model listing, and async status polling. A minor gap is the absence of cancellation or task history management for video generation, but the essential lifecycle is present.