Skip to main content
Glama
mrnh

rigor-mcp

by mrnh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Related Servers

Alternatives to rigor-mcp

No user-submitted related servers found.

    Related Servers

    • evalgateprivate

      ipezygj
      A
      license
      A
      quality
      A
      maintenance
      Eval-integrity statistics for AI benchmark claims — multiple-testing correction, power/MDE for model gaps, judge-bias and leaderboard-rank checks. Catches a benchmark number that won't survive a second look.
      9
      MIT

    • JeffersonStats

      sharabhshukla
      F
      license
      Not graded
      quality
      C
      maintenance
      Enables comprehensive statistical analysis including descriptive statistics, hypothesis testing, regression, and more via a FastMCP-based API.
      3
      -

    • genpark-study-methodology-bias

      Alpha-Park
      F
      license
      Not graded
      quality
      B
      maintenance
      Enables auditing scientific papers for methodological biases such as selection bias and p-hacking, and assessing citation credibility and research consensus.
      8
      -

    • noisefloor

      beepboop2025
      A
      license
      A
      quality
      A
      maintenance
      Checks whether a number is real or just noise: peek-safe A/B tests you can look at as often as you like without inflating false positives, two-sided change detection, and a guard for when a metric moved only because its sample size did. Zero dependencies, standard library only.
      6
      MIT

    • statlab-mcp

      good-boy4069
      A
      license
      A
      quality
      A
      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
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.1/5.0

    Scored across 37 tools

    Disambiguation5/5

    Every tool targets a distinct statistical procedure or design (e.g., paired vs. independent proportions, fixed-sample vs. sequential means, chi-square vs. exact test), and the descriptions explicitly cross-reference sibling tools to prevent misselection. Even the paired power/sample-size tools are clearly differentiated as inverse operations.

    Naming Consistency5/5

    All tool names use consistent snake_case and follow a predictable pattern: tests are named after the procedure (e.g., two_sample_t_test, mann_whitney_u), effect sizes after the statistic, and power/sample-size tools share the power_for_/sample_size_for_ prefix. The few non-test utilities (recommend_test, naive_peeking_inflation) are still stylistically consistent.

    Tool Count2/5

    37 tools is well beyond the 25+ threshold for a heavy surface, even though each tool is individually useful. The inclusion of recommend_test and pairwise_group_comparisons mitigates the burden, but the set would benefit from consolidation or a more focused scope.

    Completeness4/5

    The suite covers the common lifecycle of a statistical analysis: assumption checks, parametric/nonparametric tests, effect sizes, power/sample-size planning, multiple-comparison corrections, and pairwise follow-ups. Minor gaps remain, such as no power/sample-size calculations for ANOVA or chi-square and no explicit normality test, but agents can work around these.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources