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Scored across 30 tools
Tools are organized into clear functional groups (exploration, inference, modeling, time series, visualization, orchestration) and descriptions explicitly cross-reference each other to resolve boundary cases (e.g., plot_heatmap defers p-values to correlation_matrix; outlier_detect points time-series cases to anomaly_detect). However, genuine overlap remains: four tools handle two-group comparison (hypothesis_test, anova_test, nonparametric_test, effect_size) and correlation_matrix vs plot_heatmap compute essentially the same matrix, so an agent could hesitate on selection.
All names are clean snake_case with recognizable domain nouns, and subfamilies are internally consistent (plot_*, *_test, *_analysis, *_detect). The main deviation is verb placement: some tools are verb-first (describe_statistics, impute_missing, backtest_forecast) while others are verb-last (outlier_detect, anomaly_detect, seasonal_decompose), but the pattern remains readable and predictable.
30 tools is a heavy surface, above the 16-25 band that already feels dense, and would strain an agent's selection space. However, the server's scope is genuinely broad—six distinct statistical domains—and each tool serves a specific analytical purpose, so the count is defensible even if it approaches the upper limit of what is reasonable for one MCP server.
Coverage is comprehensive for the stated purpose: exploration (describe/type/missing/correlation/outlier/impute), inference (parametric, nonparametric, chi-square, ANOVA, CI, effect size, power), modeling (linear/logistic regression, clustering, PCA, feature importance), time series (forecast/backtest/decompose/trend/anomaly), visualization, and an orchestration planner. Minor gaps: no stationarity test (e.g., ADF) for time series, no general-purpose bar or line chart for categorical data, and no way to apply a fitted model to new data.