knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
ReliaGrowR can expose its core analysis functions as Model Context Protocol (MCP) tools, allowing AI assistants such as Claude to call them directly during a conversation. This is powered by the mcptools package from Posit.
Once configured, an AI assistant can:
Install the required packages:
install.packages("mcptools") # MCP server framework install.packages("ellmer") # Tool definition helpers (already in ReliaGrowR Suggests)
The server is started with a single call:
ReliaGrowR::rga_mcp_server()
By default this uses stdio transport (suitable for Claude Code and Claude Desktop). To use HTTP transport instead:
ReliaGrowR::rga_mcp_server(type = "http", port = 8080)
Add the server to Claude Code from your terminal:
claude mcp add -s user reliagrowR -- Rscript -e "ReliaGrowR::rga_mcp_server()"
The -s user flag stores the configuration in your user-level settings so it is
available in every project.
Add the following block to claude_desktop_config.json
(~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"reliagrowR": {
"command": "Rscript",
"args": ["-e", "ReliaGrowR::rga_mcp_server()"]
}
}
}
Restart Claude Desktop after saving.
| Tool | Function | Description |
|---|---|---|
| rga | rga() | Crow-AMSAA reliability growth model |
| nhpp | nhpp() | NHPP Power Law / Log-Linear for repairable systems |
| duane | duane() | Duane log-log regression |
| mcf | mcf() | Mean Cumulative Function (Nelson-Aalen) |
| predict_rga | predict_rga() | Forecast cumulative failures from RGA model |
| predict_duane | predict_duane() | Forecast MTBF from Duane model |
| rdt | rdt() | Reliability Demonstration Test planning |
| gof_rga | gof() | Goodness-of-fit statistics (CvM, K-S) |
With the MCP server running, you can ask Claude questions like:
"I have failure data with times [100, 200, 300, 400, 500] and failure counts [1, 2, 1, 3, 2]. Fit a Crow-AMSAA reliability growth model and forecast the cumulative failures at 1000 and 2000 hours."
Claude will call rga and predict_rga on your behalf and return the results
in plain language.
"Plan a reliability demonstration test for 90% reliability at 500 hours with 90% confidence, using a Weibull model with beta = 1.5 and 10 test units."
Claude will call rdt and explain the required test duration.
The MCP server runs R code in your local R session. Only share the server endpoint with trusted clients. For multi-user deployments, consider running the server in a sandboxed environment.
Any scripts or data that you put into this service are public.
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