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bertanucar

shewhart-mcp

by bertanucar
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Python

shewhart-mcp

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.

Related MCP server: wafer-map-mcp

License

MIT. Built by Bertan Ucar.

This server cannot be installed

A
license - permissive license
-
quality - not tested
C
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

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