A
licenseNot graded
qualityD
maintenancePowerful image generation system leveraging multiple Stable Diffusion models (flux-schnell, flux-dev, sdxl, sd3, sd15) for creating high-quality AI-generated images with precise customization.
19
MIT
FluxMCP
by AceDataCloud
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TDQS
A4/5.0
Scored across 7 tools
Disambiguation4/5
The core tools are clearly separated: generate vs edit vs video generation, and single-task vs batch task queries are explicitly distinguished. Minor overlap exists because flux_generate_video bundles several video workflows and flux_get_tasks_batch could be seen as an optimization of flux_get_task, but descriptions make the intended boundaries clear.
Naming Consistency5/5
All tools follow a consistent flux_verb_noun snake_case pattern, such as flux_generate_image, flux_edit_image, flux_get_task, and flux_list_models. The convention is predictable throughout.
Tool Count5/5
Seven tools is well-scoped for an image/video generation service. The set covers generation, editing, task polling, batch polling, and reference discovery without obvious padding.
Completeness4/5
The surface covers the main lifecycle: generate/edit media, generate video, poll tasks, batch poll, and discover models/actions. Minor gaps remain around cancellation or listing existing tasks, but core workflows appear supported.
Maintenance
ActivityActive
ResponsivenessLimited data