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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
    10
    GPL 3.0
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    Enables data analysis and visualization operations such as loading CSV/Excel/JSON files, computing summary statistics, generating charts, and exploring datasets via SSE/HTTP.
    MIT
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    Enables AI assistants to query Power BI datasets via MCP, automatically anonymizing sensitive data before it reaches the AI, and generating rich HTML reports from natural language questions.
    MIT
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    Options analytics an agent can drive: import a permitted chain, solve implied volatility, build a sixteen-Greek ladder, map dealer gamma walls, rank twenty-three structures, run a GARCH-t simulation with a convergence gate, and backtest with modelled premiums. Twelve stdio tools; every output is a schema-validated JSON file with source, assumptions and a degraded flag. Research only, no orders.
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    Enables rendering, validation, formatting, and inspection of D2 diagrams via the Model Context Protocol, using WASM for rendering without requiring the d2 binary.
    6
    MIT
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    Renders word-sized charts — sparklines, bars, bullets and 100+ more types — to self-contained SVG with generated alt text, small enough to sit inline in a model's reply or a table cell. Three tools: find the right chart for a question, get its wiring, and render it.
    3
    952 npm
    192
    MIT
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    Enables reading and analysis of vector spatial data through Claude Desktop, supporting formats like FileGDB, Shapefile, GeoJSON, and GeoPackage with tools for layer listing, schema inspection, field statistics, feature extraction, and interactive map rendering.
    9
    4
    MIT
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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.
    5
    38 npm
    9
    MIT
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    Enables LLMs to generate visual summary reports from CSV datasets using MCP Resources, Tools, and Prompts, without exposing raw data to the model.
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