shewhart-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@shewhart-mcpCreate an Xbar-R control chart for my production data."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 |
| one call: choose the right chart, check assumptions, return a structured verdict |
| I-MR, Xbar-R/S, p/np/c/u, Laney, EWMA, CUSUM by alias |
| Cp/Cpk/Pp/Ppk with confidence intervals, non-normal methods |
| normal (Howe k2) and nonparametric (Wilks) |
| 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: CalcsLive MCP Server
License
MIT. Built by Bertan Ucar.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/bertanucar/shewhart-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server