AI Integration via MCP

Overview

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:

Fit reliability growth models on data you describe
Forecast future failures or MTBF
Run goodness-of-fit tests
Plan reliability demonstration tests
Analyze repairable systems with MCF and NHPP models

Installation

Install the required packages:

install.packages("mcptools")   # MCP server framework
install.packages("ellmer")     # Tool definition helpers (already in ReliaGrowR Suggests)

Starting the MCP Server

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)

Configuring Claude Code

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.

Configuring Claude Desktop

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.

Available Tools

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)

Example Session

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.

Security Considerations

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.

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