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masterLazy

ollama-vision-mcp

by masterLazy
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    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

    A4.2/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clear, distinct purpose: list_images finds images, describe_image provides semantic description, extract_text performs OCR, and vision_status checks configuration. There is no overlap or ambiguity between them.

    Naming Consistency4/5

    Tool names predominantly follow a verb_noun snake_case pattern (describe_image, list_images, extract_text). The exception is vision_status, which is noun_noun rather than verb_noun, but the inconsistency is minor and the naming style remains uniform.

    Tool Count5/5

    With 4 tools, the server is well-scoped for a focused vision MCP. Each tool serves a necessary role in the image-analysis workflow, and the count is neither too sparse nor excessive.

    Completeness5/5

    The tool surface covers the core workflows: discovering available images, getting a semantic description, extracting text, and verifying connectivity. There are no obvious gaps that would prevent an agent from completing typical vision-related tasks.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources