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    • A
      license
      A
      quality
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      maintenance
      Enables AI agents to generate images on a local Stable Diffusion Forge Neo instance, automatically inferring prompt style and sampling parameters from the user's setup and past generations, and providing tools for LoRA search, model management, and module checks.
      10
      1
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI coding agents to control a local InvokeAI creative engine, supporting text-to-image, image-to-image, masked inpaint, upscaling, and full queue, model, gallery, board, and workflow management.
      13
      2
      MIT
    • A
      license
      A
      quality
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      maintenance
      Exposes a local Forge or AUTOMATIC1111 SDXL backend as typed image-generation tools, enabling any MCP client to generate and edit images through a deterministic, stateless interface with server-enforced SFW content.
      3
      Mozilla Public 2.0

    TDQS

    A3.7/5.0

    Scored across 18 tools

    Disambiguation4/5

    Most tools target distinct operations (sync generation, async submission, batch, compare, merge variants), and descriptions clarify the differences. A few near pairs such as generate_image/submit_generate and batch_merge_models/recipe_merge could cause misselection, but the descriptions separate them well.

    Naming Consistency3/5

    The dominant verb_noun pattern (list_models, get_job_status, merge_models) is readable, but there are notable deviations like health_check, system_info, recipe_merge, and submit_generate. The mix of verb-first and noun-first names is inconsistent enough to slow an agent down.

    Tool Count4/5

    Eighteen tools is slightly above the ideal 3-15 range, but the breadth is justified by covering generation, async jobs, model metadata, system health, and model merging. It feels like a complete API surface rather than an inflated one.

    Completeness4/5

    The surface covers generation, inpainting, async job lifecycle, model listing/metadata, schedulers, and multiple merge workflows. Obvious gaps are minor, such as the lack of a general image-to-image tool or batch async variants, but core workflows have no dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues