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.
License
MIT. Built by Bertan Ucar.
1 maintainer
Release files for shewhart-mcp 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| shewhart_mcp-0.0.1.tar.gz | 2.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| shewhart_mcp-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:4.8 kB
Release files / shewhart_mcp-0.0.1.tar.gz
| Download URL | shewhart_mcp-0.0.1.tar.gz |
|---|---|
| Size | 2.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
e24fd7784a13b65c84743c108c2e8b40d05fa2be31d0553a13f1208c4c91ab8c
|
|
BLAKE2b-256 checksum How to use checksums |
f4e4d03d1dd6c4cc09d42dacabe4d57b6c43447760a81db90b545faa1b269a21
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 12, 2026.
Transparency logRelease files / shewhart_mcp-0.0.1-py3-none-any.whl
| Download URL | shewhart_mcp-0.0.1-py3-none-any.whl |
|---|---|
| Size | 2.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
127416aaffffdca40b5f87d158660ff9b5eaf31bf22ac368ee88ca080b81d70a
|
|
BLAKE2b-256 checksum How to use checksums |
a599e0cf81650b2af67dea5fa9a4a2ce69a6138ab3d20518cef283c74c22ee36
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 12, 2026.
Transparency log
