This MCP server, developed by Isaac Wasserman, enables AI assistants like Claude to create data visualizations using Vega-Lite syntax. Built in Python, it provides two core functions: saving data tables and generating visualizations from that data. The implementation stands out by leveraging the expressive power of Vega-Lite for creating a wide range of chart types. By connecting AI capabilities with data visualization, this server enables AI systems to analyze and present data visually. It is particularly useful for scenarios like exploratory data analysis, creating reports with charts, and building AI assistants that can generate insightful data visualizations on demand.
Save a table of data aggregations to the server for later visualization. Input: name (string) - Name of the data table to be saved, data (array) - Array of objects representing the data table. Returns: success message.
Visualize a table of data using Vega-Lite syntax. Input: data_name (string) - Name of the data table to be visualized, vegalite_specification (string) - JSON string representing the Vega-Lite specification. Returns: success message with an additional artifact key containing the complete Vega-Lite specification with data or a base64 encoded PNG image of the visualization.
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