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    A demo MCP server that returns an interactive dashboard (bar chart with dataset selector) as an MCP App via the official MCP Apps extension (SEP-1865).
    1
    MIT
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    An MCP server that extracts energy-usage charts from utility-bill PDFs, returning structured time-series data and annotated images.
    1
    AGPL 3.0
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    MCP server for AI Diagram Maker — generate software engineering diagrams from natural language, code, ASCII diagram, images, or Mermaid. Inline diagram rendering using MCP apps UI and diagram URL in responses. Works with Cursor, Claude Desktop, Claude Code, and any MCP-compatible AI.
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    MIT
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    Enables creating and editing PowerPoint .pptx files without corruption, with native editable SVG shapes, glued connectors, table surgery, threaded comments, live editing, and a comprehensive 138-tool MCP server surface.
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    AGPL 3.0
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    Data-visualization MCP server for ROOT Workspace. It enables creating and iterating on charts (Vega-Lite, Python plots) with a persistent kernel and vision loop.
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    An MCP server for the Xe Currency Data API that brings live FX rates, historical analysis, and quant-flavored tools into AI tools, working out of the box with zero credentials via Frankfurter/ECB data.
    12
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    MIT
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    Enables to interact with Felt maps programmatically through an MCP server. Supports listing, retrieving details, and creating maps with natural language.
    4
    MIT
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    An unofficial MCP server for generating infographics and visuals from text using the Napkin AI API, enabling AI assistants to create professional diagrams, mindmaps, and charts.
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    MIT
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    Exposes ASCIIFlow drawing primitives as tools to enable AI assistants to generate ASCII wireframes and diagrams from natural language descriptions. It provides commands for creating canvases and drawing boxes, lines, arrows, and text using a character-grid coordinate system.
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    An MCP server for rendering common ECharts visualizations from structured tool arguments, exposing per-chart opener tools that map to independent HTML app resources.
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    MIT
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    Provides AI models with structured design guidelines and system prompts for creating consistent, high-quality interactive visualizations like charts, diagrams, and mockups. It enables on-demand loading of UI specifications to optimize token usage while ensuring visually polished and functional widget generation.
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    MIT
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    Local stdio MCP server for reviewing Apache Superset dashboards, retrieving chart data, executing SQL through SQL Lab, and creating or updating saved queries.
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    A local Python MCP server for AI-assisted development of Yandex DataLens dashboards, enabling inspection, planning, validation, and guarded application of changes.
    38
    5
    Apache 2.0