@imageat/mcp
Related Servers
Alternatives to @imageat/mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityBmaintenanceEnables image and video generation and editing through MCP tools, including image editing, upscaling, background removal, video generation, image-to-video, and video extension. Video generation runs asynchronously with job status and result retrieval.MIT
- AlicenseNot gradedqualityCmaintenanceEnables MCP-compatible clients to generate and upscale AI images, videos, music, and sound effects, manage generation jobs, access model catalogs, and track credits.3MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to generate and edit text, images, speech, music, and video, list available models, and track usage costs through a single remote MCP endpoint billed against one prepaid credit balance.MIT

pixapi-mcpofficial
AlicenseNot gradedqualityBmaintenanceEnables MCP clients to use Pixapi's AI image and video generation tools, including checking pricing and balance, starting asynchronous generation tasks, and retrieving results.36 npmMIT- AlicenseNot gradedqualityBmaintenanceEnables AI clients to create images and videos through a hosted remote MCP endpoint with browser OAuth, letting users discover available models and Quick Apps, quote credit costs, upload reference files, submit single or batch generation tasks, and retrieve finished results. It also supports task tracking, retries with consistent request IDs, and ranged downloads, while spending account credits only on actually submitted jobs.MIT
- AlicenseNot gradedqualityAmaintenanceEnables MCP-compatible clients to generate images and videos, synthesize speech, clone and design voices, and dynamically configure API interactions.549 npmMIT
TDQS
Scored across 4 tools
check_credits is clearly distinct. edit_image and generate_image could overlap, since generate_image supports reference images for image-to-image editing, but descriptions clarify that generate is text-prompt driven while edit uses specific feature IDs. Overall, boundaries are mostly clear.
All tools follow a consistent snake_case verb_noun pattern with the imageat_ prefix: check_credits, edit_image, generate_image, generate_video. The naming is predictable and uniform.
Four tools cover the core actions for an image/video generation and editing API: credit checking, image generation, image editing, and video generation. This is appropriately scoped with no redundancy.
The server covers the primary workflows: generating images and videos, editing images, and checking credits. A minor gap is the lack of a way to list available edit features, but agents can likely infer them from the documentation provided in the tool description.