List registry-backed SPSS methods available for structured execution. Use this to discover cold methods that have schemas, templates, and coverage assertions.

Get the JSON schema for a registry-backed SPSS method. Useful for structured orchestration and parameter inspection before execution.

Get support metadata for a registry-backed SPSS method, including command family, support tier, coverage assertions, and documentation tags.

Check the SPSS MCP server status: which capabilities are available (SPSS installed vs file-only mode), SPSS path, library versions, and configuration. Call this first to understand what tools are available.

List SPSS .sav files in a directory. Useful for discovering available datasets when the user hasn't specified a file path.

List all variable names and their labels from an SPSS .sav file. Optionally filter by a search term. Does not require SPSS to be installed.

Read variable names, types, labels, and value labels from an SPSS .sav file. Returns a detailed Markdown report of the file's structure. Does not require SPSS to be installed.

Read rows of data from an SPSS .sav file as a Markdown table. Optionally filter to specific variables and limit row count. Does not require SPSS to be installed.

Get a summary of an SPSS .sav file: case count, variable count, variable list, and basic descriptive statistics computed locally (no SPSS needed). Does not require SPSS to be installed.

Convert a CSV file to SPSS .sav format directly using pandas + pyreadstat — no IBM SPSS Statistics installation required. Much faster than going through SPSS syntax because it bypasses the SPSS engine entirely. Saves the .sav file next to the CSV by default, or to a custom output_path.

Execute arbitrary SPSS syntax commands and return the output as Markdown. Optionally specify a data_file to automatically prepend GET FILE. By default, this also persists .spv (SPSS viewer) and .sps (executed syntax) files. Requires IBM SPSS Statistics to be installed.

Run SPSS FREQUENCIES on one or more variables. Returns frequency tables with counts, percentages, and optional statistics. Requires IBM SPSS Statistics to be installed.

Run SPSS DESCRIPTIVES for numeric variables. Returns N, mean, std deviation, min, max, and optional statistics. Requires IBM SPSS Statistics to be installed.

Run SPSS CROSSTABS to create a contingency table between two categorical variables. Optionally includes chi-square test and row/column percentages. Requires IBM SPSS Statistics to be installed.

Run SPSS linear regression. Specify a dependent variable and one or more predictors. Returns coefficients, R-squared, ANOVA table, and significance tests. Requires IBM SPSS Statistics to be installed.

Run SPSS t-test. Supports one_sample, independent, and paired test types. Requires IBM SPSS Statistics to be installed.

Run SPSS one-way ANOVA (ONEWAY). Optionally includes post-hoc tests (e.g., TUKEY, BONFERRONI, LSD). Requires IBM SPSS Statistics to be installed.

Run SPSS CORRELATIONS to compute Pearson or Spearman correlation matrix. Requires IBM SPSS Statistics to be installed.

Run SPSS FACTOR analysis (principal components or principal axis factoring). Includes eigenvalues, variance explained, and rotated factor matrix. Requires IBM SPSS Statistics to be installed.

Run SPSS RELIABILITY analysis (Cronbach's alpha). Returns scale reliability and item statistics for psychometric workflows. Requires IBM SPSS Statistics to be installed.

Compute a scale score (SUM or MEAN) from multiple item variables, with optional reverse coding and minimum valid item count. Requires IBM SPSS Statistics to be installed.

Run common nonparametric tests in SPSS: Mann-Whitney U, Wilcoxon signed-rank, or Kruskal-Wallis. Requires IBM SPSS Statistics to be installed.

Run SPSS EXAMINE to check normality and outliers for numeric variables, with optional diagnostic plots. Requires IBM SPSS Statistics to be installed.

Run SPSS repeated-measures ANOVA (within-subject GLM). Provide within-factor name, number of levels, and one variable per level. Requires IBM SPSS Statistics to be installed.

Validate SPSS syntax without executing it. Checks for basic syntax errors. Requires IBM SPSS Statistics to be installed.

Run binary or multinomial logistic regression. Supports stepwise selection, categorical predictors, and model diagnostics. Requires IBM SPSS Statistics to be installed.

Run ordinal regression (PLUM) for ordered categorical outcomes. Supports multiple link functions and parallel lines test. Requires IBM SPSS Statistics to be installed.

Run generalized linear model (GENLIN) with flexible distribution and link functions. Supports Poisson, binomial, gamma, negative binomial, and other distributions. Requires IBM SPSS Statistics to be installed.

Run linear mixed-effects model (multilevel model) with random effects. Supports nested and crossed random effects, repeated measures structures. Requires IBM SPSS Statistics to be installed.

Run generalized linear mixed model combining GLM with random effects. Supports non-normal outcomes with hierarchical structure. Requires IBM SPSS Statistics to be installed.

Run Cox proportional hazards regression for survival analysis. Supports time-dependent covariates, stratification, and model diagnostics. Requires IBM SPSS Statistics to be installed.

Run Kaplan-Meier survival analysis with log-rank test. Produces survival curves and compares groups. Requires IBM SPSS Statistics to be installed.

Run discriminant analysis to classify cases into groups. Supports stepwise selection and cross-validation. Requires IBM SPSS Statistics to be installed.

Run hierarchical cluster analysis with dendrogram. Supports multiple linkage methods and distance measures. Requires IBM SPSS Statistics to be installed.

Run two-step cluster analysis with automatic cluster number determination. Handles large datasets and mixed variable types. Requires IBM SPSS Statistics to be installed.

Run multivariate analysis of variance (MANOVA) for multiple dependent variables. Tests multivariate effects and provides univariate follow-ups. Requires IBM SPSS Statistics to be installed.

Run univariate general linear model (GLM) with factorial designs. Supports estimated marginal means, contrasts, and post-hoc tests. Requires IBM SPSS Statistics to be installed.

Recode variable values in a .sav file. rules: list of {'old': value | [lo,hi] | [v1,v2,...] | 'ELSE', 'new': value | 'COPY' | 'SYSMIS'}. into_variables: optional list of new target variables (preserves originals). output_path: optional path to save the transformed file. Requires IBM SPSS Statistics.

Automatically recode string/categorical values into consecutive integers. order: ASCENDING (default) or DESCENDING. Requires IBM SPSS Statistics.

Create a new variable or overwrite an existing one with a computed expression. expression: any SPSS numeric expression, e.g. 'weight/(height**2)' or 'MEAN(q1,q2,q3)'. Requires IBM SPSS Statistics.

Conditionally assign a value: IF (condition) target = expression. condition: SPSS logical expression, e.g. 'age >= 30 and gender = 1'. Requires IBM SPSS Statistics.

Permanently keep only cases matching a condition: SELECT IF (condition). Use output_path to save the filtered result as a new .sav file. Requires IBM SPSS Statistics.

Sort cases by one or more variables. sort_keys: list of {'variable': name, 'order': 'A'|'D'} dicts. Requires IBM SPSS Statistics.

Weight cases by a variable (or turn weighting off with weight_variable=None). Takes effect for subsequent procedures on the same file. Requires IBM SPSS Statistics.

Temporarily filter cases by a 0/1 variable (reversible, unlike SELECT IF). filter_variable=None turns the filter off. Requires IBM SPSS Statistics.

Declare user-missing values: MISSING VALUES var (spec). missing_spec: {variable: spec}, e.g. {'age': '99'} or {'q1': 'LOWEST THRU 0; 99'}. An empty string spec ('') clears missing values with NONE. Requires IBM SPSS Statistics.

Set variable labels: VARIABLE LABELS var 'label'. labels: {variable: label}. Requires IBM SPSS Statistics.

Set value labels: VALUE LABELS var value 'label'. value_labels: {variable: {value: label}}, e.g. {'gender': {1: 'Male', 2: 'Female'}}. Requires IBM SPSS Statistics.

Change variable display formats: FORMATS var (format). formats: {variable: format}, e.g. {'income': 'F8.2', 'id': 'F4.0', 'name': 'A20'}. Requires IBM SPSS Statistics.

Declare new empty variables: NUMERIC var (F8.2) / STRING var (A20). numeric_vars: {name: format}, string_vars: {name: format}. Requires IBM SPSS Statistics.

Save the active dataset with optional rename/keep/drop: SAVE OUTFILE. rename: {old: new}, keep: variables to keep, drop: variables to drop. Requires IBM SPSS Statistics.

Combine variables across files (join by key): MATCH FILES. file_paths: >=2 .sav files; key_variables: BY variables (files must be sorted on them). output_path: merged result file. Requires IBM SPSS Statistics.

Stack cases from multiple files (concatenate/union): ADD FILES. file_paths: >=2 .sav files; key_variables: optional BY variables. output_path: stacked result file. Requires IBM SPSS Statistics.

SQL-style join of two .sav files: STAR JOIN /SELECT ... /FROM ... /JOIN ... ON key=key. base_key/join_key: matching variable names; select_fields: optional list like ['t0.age','t1.income']. Requires IBM SPSS Statistics.

Group-wise summaries: AGGREGATE /BREAK=vars /aggvar=FUNC(source). aggregations: list of {'new_var': name, 'function': MEAN|SUM|MIN|MAX|SD|N|NMISS|FIRST|LAST, 'source': var}. Requires IBM SPSS Statistics.

Rank cases: RANK VARIABLES=vars (A|D) /RANK INTO var. Options: ntiles (N-tile groups), percent (percent ranks), normal (normal scores), fraction (BLOM|TUKEY|VW|RANKIT), by_variables (within-group ranks). Requires IBM SPSS Statistics.

Transpose rows and columns: FLIP. variables: subset to flip (default all); newnames_variable: use a variable's values as new column names. Requires IBM SPSS Statistics.

Restructure long → wide format: CASESTOVARS /ID=... /INDEX=.... id_variables: case identifiers; index_variables: the repeated-measure index. output_path: restructured result file. Requires IBM SPSS Statistics.

Restructure wide → long format: VARSTOCASES /MAKE newvar FROM varlist. make_specs: list of {'new_var': name, 'variables': [var1, var2, ...]}; index_name: index variable name; id_name: case ID variable. Requires IBM SPSS Statistics.

Export procedure output directly to a file: OMS /DESTINATION FORMAT=DOC|XLS|HTML|SPV. Runs inside the same job as the procedures — call any analysis tools first, then this. NOTE: SPSS's OUTPUT EXPORT command needs a GUI Viewer, which the batch engine does not have; OMS writes the same formats without it (verified live). export_format: DOC (Word/RTF), XLS (Excel), HTML, or SPV (Viewer file).

Scatterplot: GRAPH /SCATTERPLOT(BIVAR)=y WITH x [BY panel]. Requires IBM SPSS Statistics.

Histogram: GRAPH /HISTOGRAM[(NORMAL)]=var. normal_curve=True overlays the normal curve. Requires IBM SPSS Statistics.

Boxplot by group: EXAMINE var BY catvar /PLOT BOXPLOT. NOTE: SPSS 27's GRAPH command has no /BOXPLOT subcommand (verified live, Error #17804) — boxplots are produced via EXAMINE. categorical_variable=None gives a single-variable boxplot.

Bar chart: GRAPH /BAR(SIMPLE|GROUPED|STACKED)=COUNT or STAT(var) BY catvar. statistic: COUNT (default), MEAN, SUM, or other SPSS aggregate function. Requires IBM SPSS Statistics.

Custom pivot tables: CTABLES /TABLE rowvar [stat] BY colvar. Statistics attach to rows only (e.g. income [MEAN] BY gender) — MEAN on a categorical is rejected by SPSS. statistics: COUNT, MEAN, MEDIAN, etc. Requires IBM SPSS Statistics (Custom Tables module).

K-means clustering: QUICK CLUSTER varlist /CRITERIA CLUSTER(k) MXITER(n). save_cluster_variable: saves cluster membership as a new variable. print_anova: adds the ANOVA table. Requires IBM SPSS Statistics.

Distance/similarity matrix: PROXIMITIES varlist /MEASURE=EUCLID. measure: EUCLID, SEUCLID, COSINE, CORRELATION, BLOCK, CHEBYCHEV, MINKOWSKI(p), POWER(p,r), CHISQ, PH2. view: CASE (rows) or VARIABLE (columns). Requires IBM SPSS Statistics.

Box-Jenkins ARIMA time-series model: ARIMA depvar /MODEL=(p,d,q). p/d/q: autoregressive, difference, moving-average orders. log_transform: None, 'LG10' (base-10), or 'LN' (natural). Requires IBM SPSS Statistics.

Ratio statistics: RATIO STATISTICS num WITH den [BY group] /PRINT=stats. statistics: MEAN, MEDIAN, MIN, MAX, STDDEV, AAD, COD, PRD, CIN(95), etc. Requires IBM SPSS Statistics.