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Glama
lerlerchan

rstudio-mcp-server

by lerlerchan

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
r_executeB

Execute R code and return the output. Useful for running R commands, data analysis, or quick tests.

r_test_packageB

Run tests for an R package using devtools::test() or testthat. Great for TDD workflow.

r_test_fileB

Run a specific test file using testthat::test_file()

r_check_packageB

Run R CMD check on a package using devtools::check(). Essential for package development.

r_document_packageB

Generate documentation for an R package using devtools::document() (roxygen2)

r_build_packageC

Build an R package using devtools::build()

r_install_packageB

Install an R package from CRAN or local path

r_load_allB

Load all functions in an R package for interactive development using devtools::load_all()

r_list_packagesB

List all installed R packages

r_workspace_lsB

List objects in the R workspace

jamovi_build_moduleC

Build a jamovi module using jmvtools

jamovi_check_moduleB

Check a jamovi module for common issues

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.5/5.0

Scored across 12 tools

Disambiguation5/5

Each tool targets a distinct action: jamovi_* for module tasks, r_* for R package development and general execution. Even closely related tools like r_test_file and r_test_package are clearly differentiated by their scope.

Naming Consistency4/5

Most tools follow a prefix_verb_noun pattern (e.g., r_build_package, r_check_package). Minor deviations like 'r_execute' (no noun) and 'r_workspace_ls' (noun_verb) are still clear and do not cause confusion.

Tool Count5/5

With 12 tools, the set covers jamovi module work and comprehensive R package development (build, check, document, install, test, load) without being bloated. Each tool serves a clear purpose.

Completeness4/5

The R package development tools adequately cover the core lifecycle (build, check, document, test, install), but missing operations like package removal or update are minor gaps. Jamovi tools are limited to build and check, which is acceptable for a niche focus.

Maintenance

ActivityInactive
ResponsivenessNo issues