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    Enables natural-language interaction with Ladybug Tools for building performance simulation, 3D modeling, and data visualization, allowing agents to perform complex environmental analysis tasks without CAD software.
    3
    GPL 3.0
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    A Model Context Protocol server for interacting with Lightdash, enabling AI assistants to discover data, create charts, and manage dashboards programmatically.
    28
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    MIT
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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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    A Model Context Protocol (MCP) server that exposes tools for exploring and querying SQLite and PostgreSQL databases. It allows Large Language Models (LLMs) to inspect table structures, perform statistical profiling, generate entity-relationship diagrams, and execute queries safely.
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    MIT
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    A Model Context Protocol server providing mathematical and scientific computing capabilities via NumPy, pandas, SciPy, and Matplotlib, with 19 tools for linear algebra, statistics, numerical methods, data processing, and plotting.
    19
    MIT
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    Enables AI assistants to interact with inSCADA systems via the Model Context Protocol, providing 39 tools for live data, alarms, scripts, historical analysis, charts, and more.
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    56
    MIT
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    A Model Context Protocol server for Metabase that enables AI assistants to interact with Metabase instances, providing 418 tools across 58 categories for database, card, dashboard, collection, user, permissions, and more management.
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    MIT
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    Provides advanced charting widgets (uPlot time series, ECharts box plots and parallel coordinates) for Urano Desktop/Cloud via MCP tools that build uiSpec JSON for rendering.
    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.
    MIT
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    Exposes tools and resources for human-supervised geological modelling from borehole data, including validation, 3D implicit model construction with GemPy, and uncertainty analysis, with a deterministic audit trail.
    MIT