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    • A
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      An MCP server that adds visual understanding to text-only LLMs via image understanding, OCR, and image comparison tools, with multi-provider fallback and context-aware Focus Hint for precise descriptions.
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    • A
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      A multi-model vision MCP server that gives image understanding to AI coding models lacking native vision, letting them analyze screenshots of code, errors, UI, and documents or perform OCR. It routes requests through major vision LLM providers and can be shared over local networks via HTTP or Docker.
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    • A
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      A multi-model vision MCP server that gives image understanding to AI coding models lacking native vision, letting them analyze screenshots, error images, UIs, documents, and OCR content through a single unified tool. It supports several mainstream vision LLM providers plus any OpenAI-compatible endpoint, with automatic image cropping, compression, and retry handling.
      1,104 npm
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    • A
      license
      A
      quality
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      MCP server that provides vision understanding to non-multimodal agents via 4 tools (analyze/describe/OCR image, list providers), supporting 13 vision providers with automatic fallback and secure URL handling.
      4
      281 npm
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    TDQS

    C2.4/5.0

    Scored across 10 tools

    Disambiguation2/5

    Several tools have direct aliases (analyze_image/image_analysis, analyze_video/video_analysis) causing ambiguity. The other image-analysis tools (data visualization, UI diff, error screenshot, diagram understanding) overlap in scope but have distinct purposes, so some differentiation is possible.

    Naming Consistency2/5

    Most tools follow a verb_noun pattern (analyze_data_visualization, analyze_image, extract_text_from_screenshot), but several deviate (ui_diff_check, ui_to_artifact, image_analysis, video_analysis). The mixed conventions and presence of aliases make naming inconsistent.

    Tool Count4/5

    Ten tools is within a reasonable range for a vision server, but two are redundant aliases, effectively reducing the count to eight. The set is not bloated, but the aliases needlessly inflate the number.

    Completeness4/5

    The server covers a broad range of vision tasks: general image/video analysis, chart understanding, UI regression, OCR, error diagnosis, diagram comprehension, and UI conversion. Missing some common vision features like object detection or face analysis, but for its UI/development focus, the coverage is solid.

    Maintenance

    ActivityStale
    ResponsivenessNo issues