Skip to main content
Glama

Related Servers

Alternatives to runninghub-image

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables image understanding, OCR, multi-image comparison, and AI image generation through pluggable models, supporting tasks like visual analysis, text extraction, and image synthesis.
      1
      MIT
    • F
      license
      A
      quality
      D
      maintenance
      Enables AI image generation, editing, and composition using Google's Gemini image models (Nano Banana Pro and Nano Banana). Supports text-to-image generation, multi-image composition, flexible aspect ratios, high-resolution output up to 4K, and real-time information grounding.
      4
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables generation and enhancement of videos through a unified entry point to 200+ video models (Kling, Hailuo, Seedance, Vidu, Wanxiang), covering text-to-video, image-to-video, start-end frame interpolation, reference-to-video, video upscaling, and digital-human talking-head clips. Built for short-video operations, ad placement, and drama teams that would otherwise juggle several platforms for a single clip.
      MIT

    TDQS

    A3.7/5.0

    Scored across 7 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes: submit/query/wait tasks, upload/download files. However, search_models and list_models both retrieve the model catalog, and an agent may need to read descriptions carefully to choose between keyword search and category browsing. The overlap is minor but present.

    Naming Consistency5/5

    All tool names follow the same predictable pattern: runninghub_ prefix plus verb_noun (search_models, list_models, submit_task, query_task, wait_task, upload_file, download_file). The snake_case convention is consistent throughout with no deviations.

    Tool Count5/5

    Seven tools is a well-scoped set for an image generation service. Each tool covers a necessary step in the workflow: discovery, submission, monitoring, and file transfer. No tool feels redundant or excessive.

    Completeness4/5

    The surface covers the core lifecycle: finding models, submitting tasks, polling for results, and uploading/downloading files. Minor gaps exist, such as no explicit task cancellation and no tool to submit workflow/AI-app tasks despite query_task mentioning legacy support for them.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues