Enables MCP-compatible AI clients to validate healthcare claims data quality by running completeness, integrity, and temporal checks on CSV files via five callable tools, including profiling and full scans.
MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.
Enables AI assistants to validate CSV exports against schemas, infer schemas from example files, profile datasets, and diff before/after exports for lab/LIMS data-quality checks.
Enables AI clients to perform data analysis on CSV datasets through tools for dataset info, summaries, missing value detection, regional sales filtering, and column statistics.