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    | 地価トレンド予測 | 新宿区の5年後地価をAI予測。CAGR・投資シグナル付き | | 企業立地需要分析 | 名古屋市中区のオフィス・工場需要スコアを算出 | | ファミリー向け適性評価 | 横浜市西区の教育・安全・医療スコアを総合評価 | | ポートフォリオ最適化 | 東京・大阪・埼玉の3エリアに投資配分を最適化 | | What-If シナリオ分析 | 大阪市中央区で新駅開設シナリオを試算 | | 店舗出店適地評価 | 福岡市博多区の人流・商業施設・交通データで出店適性を判定 |
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    AGPL 3.0
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    An MCP server that extracts energy-usage charts from utility-bill PDFs, returning structured time-series data and annotated images.
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    AGPL 3.0
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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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    MIT
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    A TradingView-style market research and charting MCP server that provides tools for market data, indicators, watchlists, and local HTML chart rendering without scraping TradingView.
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    A virtual statistician MCP server that provides real statistical methods—design of experiments, hypothesis testing, regression, SPC, MSA—via tested Python libraries, with plain-language interpretations and plotted outputs.
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    MIT
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    Enables Claude to create and edit Figma designs in real time through MCP tools, allowing natural language commands for generating slides, charts, and other elements.
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    MIT
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    Launches/connects to the visible draw.io desktop editor and edits its active graph model in real time, allowing AI agents to draw scientific figures step by step.
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    MIT
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    Enables time series analysis following Box-Jenkins-Treadway methodology, supporting guided or autonomous modes for model identification, estimation, and diagnosis via an LLM.
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    GPL 2.0
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    Enables AI assistants to create interactive charts, diagrams, and tables displayed on a real-time dashboard, supporting multiple data sources with privacy-focused local execution.
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    MIT