Skip to main content
Glama

Related Servers

Alternatives to StatsPAI

No user-submitted related servers found.

    Related Servers

    • F
      license
      Not graded
      quality
      D
      maintenance
      An MCP server that exposes causal inference methods (difference-in-differences, synthetic control, propensity matching, and assumption checks) as callable tools, enabling AI agents to run deterministic statistical analyses instead of computing them inline.
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to run zero-dependency statistical modeling and data analysis through MCP, including multivariate linear regression via gradient descent, anomaly detection, time-series forecasting, hypothesis testing, and PCA dimensionality reduction.
      7
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to perform reproducible, verifiable statistical analysis through 25 deterministic tools for descriptive statistics, hypothesis testing, regression, clustering, time-series forecasting, and Chinese-labeled plotting.
      30
      1
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables comprehensive statistical analysis including descriptive statistics, hypothesis testing, regression, and more via a FastMCP-based API.
      3
      -

    TDQS

    B3.4/5.0

    Scored across 45 tools

    Disambiguation3/5

    Descriptions work hard to cross-reference each other (e.g., brief says 'Same output as brief_result'; honest_did points to honest_did_from_result), but several pairs genuinely overlap: brief/brief_result, audit/audit_result, sensitivity/sensitivity_from_result, iv vs ivreg, and honest_did vs honest_did_from_result. The advisory cluster (detect_design, check_identification, preflight, recommend, route_estimator, causal) is also hard to separate without reading ordering hints, though the descriptions do provide them.

    Naming Consistency3/5

    Mostly snake_case, but two conventions coexist: verb_noun for plumbing (load_data, transform_data, search_functions, plot_from_result) and bare estimator/package names for methods (did, iv, dml, synth, match, sdid, feols, ivreg, rdrobust, ebalance). The result-accessor suffix is also inconsistent, mixing '_result' (brief_result, audit_result) with '_from_result' (honest_did_from_result, sensitivity_from_result, vcov_from_result, plot_from_result).

    Tool Count2/5

    45 individually listed tools is heavy for any single server, and several slots are redundant duplicates (brief vs brief_result, audit vs audit_result, sensitivity vs sensitivity_from_result) rather than earned surface. The search_functions/describe_function/call_function escape hatch already covers the ~1,200-function registry, so the long tail of listed estimator tools is partly unnecessary.

    Completeness4/5

    Coverage of the causal-inference lifecycle is strong: data load/transform/profile, design detection and preflight, estimators across DID/IV/RD/matching/DML/synth, robustness and sensitivity, pipelines, plotting, interpretation, and citation lookup. The main gap is state management — there is no way to list existing data_ids or result_ids, or to delete/export them, which forces agents to carry handles out-of-band.

    Maintenance

    ActivityActive
    ResponsivenessLimited data