Shewhart

An MCP server that exposes shewhart, the statistical process control library for Python, as tools for AI agents.

The reasoning: agents asked about process data tend to generate their own statistics, and generated statistics fail silently. Calculation belongs in a deterministic, versioned, validated tool that the agent calls. The agent interprets; validated code calculates.

Status

In development. This release reserves the package name; the first working server ships shortly, with these tools:

Tool	Purpose
review	one call: choose the right chart, check assumptions, return a structured verdict
control_chart	I-MR, Xbar-R/S, p/np/c/u, Laney, EWMA, CUSUM by alias
capability	Cp/Cpk/Pp/Ppk with confidence intervals, non-normal methods
tolerance_interval	normal (Howe k2) and nonparametric (Wilks)
fit_baseline / evaluate_baseline	freeze control limits, judge new data against them

Every result carries provenance (library version, input hash, timestamp) and is validated against published reference values, including NIST-certified datasets, in CI.

License

MIT. Built by Bertan Ucar.