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root-ext-viz

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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

    A4.2/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool addresses a distinct stage of the visualization workflow: profiling, loading, state inspection, Python execution, reset, spec creation, export, and recipes. No two tools have overlapping purposes; data_profile describes a file, data_load imports it, and chart_spec creates a chart while chart_export converts existing specs.

    Naming Consistency4/5

    Tool names predominantly use snake_case with grouped prefixes (data_*, session_*, chart_*), but not all follow a strict verb_noun pattern (e.g., session_state, chart_spec, viz_recipes). Minor deviations in parts of speech do not significantly impede predictability.

    Tool Count5/5

    Eight tools is within the ideal range for a visualization server. Each tool covers a necessary function—data intake, kernel control, transformation, chart authoring, and output—without redundancy or bloat.

    Completeness5/5

    The tool surface covers the full lifecycle from data profiling and loading, to transformation via Python, to chart specification, rendering, and export, plus session management and recipe templates. There are no evident gaps for the stated purpose of creating and exporting visualizations.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources