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jrenaldi79

Northwestern AI image MCP

by jrenaldi79
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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

    A4.3/5.0

    Scored across 8 tools

    Disambiguation4/5

    Each tool targets a distinct action or resource: authentication (auth_login, auth_logout, account_status), model discovery (list_image_models, get_image_model), and image operations (generate_image, edit_image, remask_image). The only pair with potential overlap is list_image_models vs get_image_model, but they are clearly differentiated as list vs detail. No tool boundaries are confusing.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern: auth_login, list_image_models, get_image_model, generate_image, auth_logout, account_status, edit_image, remask_image. The prefix 'auth_' and 'image' nouns are used predictably.

    Tool Count5/5

    Eight tools are well-scoped for an image generation and editing server with authentication. Each tool has a clear purpose and no redundancy; the set covers the full workflow from sign-in to model discovery to image generation, editing, and local re-masking.

    Completeness5/5

    The surface covers the complete lifecycle: authentication (login, logout, status), model discovery (list, get), image generation, editing with masking, and free local re-masking. It even anticipates advanced use cases like mask adjustments without extra cost. No obvious gaps for the stated domain.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources