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.
20
MIT
FluxMCP
by AceDataCloud
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TDQS
A4/5.0
Scored across 7 tools
Disambiguation4/5
flux_generate_image and flux_edit_image are clearly distinguished by their generation vs. editing semantics, and flux_get_task vs. flux_get_tasks_batch differ by singular/plural. However, the action of checking generation status is split across three tools (get_task, get_tasks_batch, and the generate_* tools that return task IDs), which could create minor confusion about when to poll.
Naming Consistency5/5
All tools follow a consistent flux_verb_noun pattern: get_task, edit_image, get_tasks_batch, generate_video, generate_image, list_actions, list_models. The only variation is the plural 'tasks' in get_tasks_batch, which is a natural and readable exception.
Tool Count5/5
Seven tools is well-scoped for an image/video generation service. It covers generation, editing, status checking, batch status, and two reference lists without redundancy.
Completeness4/5
Core workflows are covered: generate image/video, edit image, poll status (single and batch), and list models/actions. Minor gaps include no explicit cancellation or deletion of tasks, and no way to list past tasks, but agents can work around these.
Maintenance
ActivityActive
ResponsivenessUnresponsive