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    TableCharts MCP Server gives any LLM assistant the ability to instantly convert tabular data into beautiful, hosted, interactive dashboards. Simply provide JSON rows, raw CSV text, or a public URL (Notion page, Google Sheet, or Salesforce report), and get back a shareable dashboard URL plus an embeddable iframe code — all in one tool call. Supports 6 chart types: bar, line, area, pie, scatter, a
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    17
    MIT
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    Local MCP server for YueShu Graph 5.3 enabling safe GQL validation and execution, schema discovery, and structured graph/chart results through Codex.
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    An MCP server that enables AI assistants to create interactive visualizations, perform statistical analysis, run auto-EDA, and build dashboards using the HoloViz ecosystem with self-contained HTML output.
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    MIT
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    A modern Python MCP server for rendering customizable charts (line, bar, pie, scatter, area, combined dashboards) with Plotly, supporting export to PNG, SVG, and base64, and terminal charts with ANSI output.
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    MIT
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    Enables AI agents to drive IBM SPSS Statistics for statistical analysis and publication-quality chart generation through natural language, returning structured results and ensuring safe execution.
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    MIT
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    Enables MCP-compatible agents to render privacy-first, deterministic Chart.js charts locally as PNG, SVG, PDF, or JSON, with configurable Sotheby's-inspired editorial themes per session.
    MIT
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    Enables AI assistants to generate and render individual and composite Human Design charts, explore authorized chart and library data, and manage account usage and Website Builder projects with secure OAuth and entitlement filtering.
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    MIT
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    A TypeScript/Node.js MCP server that wraps the Metabase REST API, enabling AI agents to execute queries, explore schemas, and build dashboards through structured tool calls.
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    MIT
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    Enables conversational patent data analysis through a set of tools for trend analysis, clustering, word cloud generation, and more. Allows natural language queries to explore patent datasets with structured results and visualizations.
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    AGPL 3.0
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    MCP server for controlling jamovi from MCP clients. It starts a local jamovi engine process and exposes tools for opening datasets, reading/writing data, running analyses, exporting results, and saving .omv files.
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    MIT
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    Enables LLM clients or shell users to read and control a live TradingView Desktop chart, including chart state, OHLCV and indicator values, Pine Script editing/compiling, drawings, alerts, bar replay, and screenshots via the Chrome DevTools Protocol.
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    MIT
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    Enables connecting to any SQL database, exploring schemas, running queries, and visualizing results with interactive charts from Claude Desktop.
    MIT