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karond-is-me

vision-mcp

by karond-is-me
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    • llm-vision-mcp

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    • mcp-six-eyes

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      MCP server that gives text-only AI agents the ability to understand images via vision tools, including multi-image analysis, OCR, comparison, and structured extraction. It uses providers like OpenAI, Anthropic, Gemini, and OpenRouter to return plain text descriptions.
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    Deploy Server
    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

    A3.9/5.0

    Scored across 12 tools

    Disambiguation4/5

    The vision_ tools are mostly distinct: qa asks questions, describe gives faithful descriptions, detect returns bounding boxes, and ocr extracts text. The image_ tools are clearly separated by operation. There is slight overlap between vision_qa and vision_describe, but the parameter and return descriptions make their use cases reasonably distinguishable.

    Naming Consistency4/5

    Tool names follow a clear two-prefix convention: vision_* for understanding tasks and image_* for manipulation/annotation tasks. Minor deviations exist—vision_qa and vision_ocr are noun-like rather than verb-like, and image_get_metadata uses get while other image tools do not—but overall the naming is readable and predictable.

    Tool Count5/5

    Twelve tools is a well-sized surface for a vision MCP server: four vision analysis tools and eight image processing/annotation tools. Each tool covers a distinct operation without bloat.

    Completeness4/5

    The tool set covers the core vision workflow well: understand, describe, detect, OCR, transform, and annotate images. Minor gaps like explicit format conversion or color/quality adjustments exist, but they are not critical for typical visual QA and image inspection use cases.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources