MCP server exposing shewhart's statistical process control analyses as tools for AI agents.
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# shewhart-mcp An MCP server that exposes [shewhart](https://github.com/bertanucar/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](https://github.com/bertanucar).
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