Provides governed MCP tools for validating, explaining, and remediating clinical supply chain data quality across Bronze, Silver, and Gold layers on Azure Databricks, with data contracts and an evaluation harness.
Enables AI applications to query and retrieve healthcare data (patients, conditions, observations, medications) from a public FHIR R4 server via MCP tools.
Enables users to validate MCP servers, skills, extensions, and packages for schema, security, functional, and semantic quality directly from their MCP client.
Enables any MCP client to run a complete data-science pipeline on a CSV: exploration, cleaning, model comparison, training, tuning, and plain-language analysis. Exposes nine tools that turn raw data into trained models and reports.
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.