Skip to main content
Glama

Related Servers

Alternatives to fapihub-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to process images locally via file paths—converting, resizing, removing backgrounds, smart cropping, upscaling, reading or stripping metadata, and batch processing—without files ever leaving the device.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to perform local image operations such as circle cropping, cropping, resizing, compressing, converting, and inspecting images without uploading files or making network calls.
      7
      47 npm
      MIT
    • A
      license
      C
      quality
      B
      maintenance
      Enables AI agents and users to edit images through natural language, performing layered, non-destructive operations like masks, clipping masks, blend modes, filters, generative fill, image-to-image, background removal and upscaling, either locally or via the user's own API keys. Agents can preview rendered results, measure image properties, review their own work and export finished images through 62 tools shared with the editor's UI.
      62
      50 PyPI
      2
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Local file tools for agents. Read and convert documents (DOCX, PDF, HWP, HWPX, EML), edit PDFs, resize and clean images, cut out backgrounds, make QR codes. Nothing is uploaded.
      6
      5
      MIT

    TDQS

    A3.7/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool has a clearly distinct image-editing operation: background removal, mask creation, background blur, solid color replacement, gradient replacement, shadow addition, and usage inspection. While blur/color/gradient all manipulate backgrounds, their descriptions make the output differences explicit, and create_mask versus remove_background is also clear.

    Naming Consistency4/5

    Most tools follow a verb_noun pattern such as remove_background, create_mask, blur_background, color_background, and add_shadow. The one deviation is gradient_background, which reads more like noun_noun than verb_noun, but the overall convention remains readable and predictable.

    Tool Count5/5

    Seven tools is well-scoped for an image background processing API. Each tool corresponds to a meaningful operation, and there is no redundant filler.

    Completeness4/5

    The surface covers the core background-manipulation workflows: removal, masking, blur, solid color, gradient, shadow, plus usage inspection. A custom image background replacement or compositing tool would round it out further, but the existing set covers the primary domain operations.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues