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datawrapper-mcp

by palewire
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Python
Hybrid

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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

    A3.8/5.0

    Scored across 9 tools

    Disambiguation5/5

    Each tool has a distinct role in the Datawrapper lifecycle: discovery (list_chart_types, get_chart_schema), account check, create, publish, get, update, delete, and export. There is no meaningful overlap between chart creation, publishing, exporting, or schema exploration. The workflow order is made explicit in descriptions.

    Naming Consistency5/5

    All tool names use snake_case with clear verb_noun patterns such as create_chart, get_chart, update_chart, delete_chart, publish_chart, and export_chart_png. The only slight variation is check_datawrapper_connection, but it still follows snake_case and remains readable. The set is highly predictable.

    Tool Count5/5

    Nine tools is well-scoped for a chart creation and management integration. Each tool covers a necessary operation without obvious redundancy. The count stays comfortably within the ideal 3-15 range.

    Completeness4/5

    Core chart lifecycle operations are covered: creation, retrieval, update, deletion, publishing, export, schema discovery, and connection checking. The main gap is the lack of a list_charts or search tool for finding existing chart IDs, which would help agents manage prior work. This is a minor gap that can be worked around when chart IDs are known.

    Maintenance

    ActivitySlowing
    ResponsivenessUnresponsive

    Resources