R MCP Server

# R-Server MCP A specialized Model Context Protocol (MCP) server that enables AI models to generate data visualizations using R's ggplot2 library and

Local serverstdioGo

What is the R MCP server?

Most cloud and infrastructure work still happens through a UI a human drives. R MCP server moves it into the conversation instead. # R-Server MCP A specialized Model Context Protocol (MCP) server that enables AI models to generate data visualizations using R's ggplot2 library and execute R scripts. ## Overview This MCP server provides a streamlined interface for.

The short version

This MCP server provides a streamlined interface for creating statistical visualizations and executing R scripts without requiring direct access to an R environment. It exposes two MCP tools: - render_ggplot: Generates visualizations from R code containing ggplot2 commands - execute_r_script: Executes any R script and returns the text output

  • ggplot2 Rendering — Execute R code containing ggplot2 commands and return the resulting visualization
  • R Script Execution — Execute any R script and return the text output
  • Format Options — Support for PNG, JPEG, PDF, and SVG output formats
  • Customization — Control image dimensions and resolution
  • Error Handling — Clear error messages for invalid R code or rendering failures
  • MCP Protocol Compliance — Full implementation of the Model Context Protocol

What it needs from you

  • Go 1.22 or later - R 4.0 or later with ggplot2 package - Docker (for containerized execution)

Getting it running

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.

How it compares

Plenty of cloud and infrastructure servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. It is maintained by gdbelvin; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Things to watch

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

How to install the R MCP server

{
  "mcpServers": {
    "r-server": {
      "command": "/path/to/r-server",
      "disabled": false,
      "autoApprove": []
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Go 1.22 or later - R 4.0 or later with ggplot2 package - Docker (for containerized execution)

Frequently asked questions

It provides two MCP tools: `render_ggplot` to create plots from ggplot2 code and return them as image files, and `execute_r_script` to run any R code and capture text output. Both are accessed through the stdio MCP transport.