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data-science-mcp

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables statistical forecasting and anomaly detection over numerical time-series data using Holt linear smoothing, multi-step projections, and variance-based confidence bands.
      7
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables time series analysis following Box-Jenkins-Treadway methodology, supporting guided or autonomous modes for model identification, estimation, and diagnosis via an LLM.
      35
      GPL 2.0
    • A
      license
      A
      quality
      B
      maintenance
      Enables users to perform deterministic time series forecasting through Claude by running reproducible Python statistical and foundation models, providing tools for loading data, cross-validation, forecasting, anomaly detection, and exporting re-runnable manifests without any LLM involvement.
      8
      MIT
    • F
      license
      A
      quality
      C
      maintenance
      Enables demand forecasting and replenishment recommendations using statistical models (Syntetos-Boylan classification, AutoETS, TSB) and provides tools for forecasting, evaluation, and order quantity calculation.
      6
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to forecast numerical trends with zero-dependency Holt linear exponential smoothing, multi-step horizons, variance confidence bands, and supporting statistical anomaly detection, regression, hypothesis testing, and PCA.
      7
      MIT