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Image Label MCP Server

Image Label MCP Server

by sachinbkale27
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

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    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.9/5.0

    Scored across 23 tools

    Disambiguation4/5

    Most tools have clearly distinct resource+action boundaries across image management, annotation editing, segmentation, slide analysis, and export. A few adjacent tools such as add_annotations vs segment_objects/detect_nuclei, and upload_slide auto-starting analysis vs analyze_slide, could be confused at first glance, but the descriptions cross-reference them.

    Naming Consistency5/5

    All tool names use lower snake_case with a predictable verb_noun shape, e.g. list_images, upload_image_from_url, export_dataset. Suffixes such as _from_url and _slide_analysis are used consistently and remain readable.

    Tool Count3/5

    At 23 tools, the set is in the heavy 16-25 range. The broad scope of general image labeling plus specialized pathology and whole-slide analysis makes many tools defensible, but the surface still feels somewhat over-scoped for one server.

    Completeness4/5

    Core image lifecycle and annotation lifecycle are well covered: upload/list/get/view/update metadata, add/replace/remove annotations, segmentation, histology analysis, and export. There are still noticeable gaps such as no delete_image/delete_slide and no list_slides operation beyond retrieving a slide analysis.

    Maintenance

    ActivityNo data
    ResponsivenessSyncing

    Resources