nhanes-mcp
Related Servers
Alternatives to nhanes-mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables natural-language access to R maftools cancer genomics analyses, including mutation summaries, oncoplots, cohort comparisons, mutation signatures, clinical enrichment, survival analyses, and copy-number visualization.MIT
- FlicenseAqualityDmaintenanceEnables interaction with synthetic NIH-style clinical research data through tools for searching publications, querying patient metadata, analyzing AAA measurements, and retrieving protocol guidance.5-
- AlicenseNot gradedqualityDmaintenanceEnables natural language exploration of OMOP CDM databases for concept discovery, patient count queries, and cohort SQL generation with support for multiple database backends.1MIT
- AlicenseAqualityDmaintenanceEnables natural language queries of U.S. Census Bureau data, translating plain English questions into proper API calls and returning demographic, economic, and housing statistics with proper statistical interpretation and context.320MIT
- AlicenseAqualityCmaintenanceEnables natural language discovery, querying, and analysis of Thailand's official statistics from the National Statistical Office via SDMX REST API. It provides tools for searching dataflows, exploring structures, and fetching data with caching and bilingual support.8MIT
- AlicenseAqualityCmaintenanceEnables preparing data, building and running Mplus input files, and reading the output back as tables, including fit indices, parameter estimates, and warnings.10MIT
TDQS
Scored across 15 tools
Each tool maps to a distinct NHANES workflow step: discovery, variable lookup, dataset construction, cleaning, derivation, and a specific survey estimator. Even similar pairs like describe_variable/describe_dataset and survey_estimate/survey_frequency are separated by clear resource and statistical-output differences.
The tools overwhelmingly follow a lowercase snake_case verb_noun pattern such as list_files, build_dataset, and export_dataset. Minor deviations like analysis_guidance and the survey_* family break the strict verb-first style, but the naming remains predictable and readable.
Fifteen tools is at the upper edge of the ideal range, but every tool earns its place by covering a necessary stage in the NHANES analysis pipeline. There is no redundancy or filler.
The toolkit covers the full analytic lifecycle: data discovery, codebook inspection, dataset assembly, missing-value handling, variable derivation, survey-weighted descriptive statistics, regression, survival analysis, and export. The analysis_guidance tool also addresses domain-specific estimation rules that would otherwise be a critical gap.