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  1. Home
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  3. MCPR
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Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 4:45:42 PM

MCPR

User RatingsBe the first to rate and review this MCP server!
View Repository26 GitHub StarsTotal stargazers on GitHub for the source repository (26 stars).Visit Website
rcode-executiondata-scienceplottingmcp

Connects AI agents to persistent R sessions for code execution, plotting, workspace inspection, and optional session attachment.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON â–¾
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for phisanti/MCPR, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives🧮 More in Data Science Tools

Overview

phisanti/MCPR MCP server lets AI agents work inside persistent, interactive R sessions instead of launching a fresh Rscript process for every command. It exposes R code execution, plot rendering, environment inspection, and optional session management through JSON-RPC 2.0 over nanonext sockets. Reach for it when an analysis depends on accumulated workspace state, iterative modelling, or collaboration with an existing human-controlled R session.

Use cases

•Run multi-step R analyses while preserving workspace state
•Execute R code and inspect structured results
•Generate plots for users or agent analysis
•Attach an agent to an existing interactive R session
•Inspect R session objects and terminal output

Key features

•Persistent private R workspace
•Arbitrary R code execution
•Agent and user plot targets
•Interactive R session management
•Session and terminal inspection
•JSON-RPC communication over nanonext

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCPR.

Extracted Tool Capabilities
Persistent private R workspace
Arbitrary R code execution
Agent and user plot targets
Interactive R session management
Session and terminal inspection
JSON-RPC communication over nanonext

How MCPR works

What phisanti/MCPR MCP server does

phisanti/MCPR MCP server connects an MCP client to a live R runtime. The default server process is a private R session belonging to the agent, so objects created during one tool call remain available to later calls. This supports workflows such as loading packages, transforming data, fitting models, checking results, and refining plots without rerunning a complete script each time.

The package also supports collaboration with a human R session. A person can start an MCPR session from an interactive R console, after which the agent can discover and attach to it. The server is described as experimental in the project materials.

How it works

The client launches MCPR::mcpr_server() as an R process. MCPR communicates using JSON-RPC 2.0 over nanonext sockets. Agent-facing functions are exposed as separate MCP tools rather than as one general protocol endpoint.

Ordinary operations use the currently active session and do not take a session identifier. Session routing is controlled independently through manage_r_sessions. The default route is the agent’s private session; joining another session changes where ordinary tools execute until the agent detaches.

Plot output can use httpgd for off-screen rendering when available. MCPR can fall back to standard R graphics devices, and its graphics handling includes token management for image responses.

Setup and configuration

R must be installed before MCPR. The package is installed from GitHub with remotes::install_github("phisanti/MCPR"); the README also shows installing remotes first when it is not present.

After installation, install_mcpr(agent = "claude") can configure the server for supported agents. The documented agent names are Claude, Gemini, Copilot, and Codex. Manual Claude Desktop configuration uses an R command with the following arguments:

config.json
{
  "command": "R",
  "args": ["--quiet", "--slave", "-e", "MCPR::mcpr_server()"]
}

Configuration locations vary by operating system and client. Claude Desktop, Gemini, Copilot, and Codex each have documented configuration paths in the project README.

Tools and capabilities

phisanti/MCPR MCP server documents these core tools:

  • execute_r_code(code) evaluates arbitrary R expressions and returns structured results, output, warnings, and errors.
  • show_plot(expr, target, width, height, format) creates plots. User-targeted output displays through the active graphics device; agent-targeted output returns an encoded image with metadata and token information.
  • manage_r_sessions(action, session) lists sessions, joins a human session, starts an MCPR-owned secondary session, detaches to the private session, or closes an MCPR-owned secondary session.
  • view(what, max_lines) provides environment introspection and debugging. The documented options include session summaries and terminal output.

Limitations and notes

MCPR is intended for stateful, iterative R work, not merely isolated command execution. Attaching to an existing R console requires the user to start that session with mcpr_session_start() before the agent can join it. The README does not document authentication, hosted deployment, or remote service credentials. Support for graphics depends on the available R graphics setup: httpgd is optional because standard graphics devices provide a fallback. The project labels its lifecycle as experimental, so client configuration details and behaviour may change.

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
26
Stargazers on the source repository.
Last commit
7d ago
Most recent push to the default branch.
Directory activity
3 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about MCPR

Install R, then install the package from GitHub with remotes::install_github("phisanti/MCPR"). Run install_mcpr(agent = "claude") for supported automated configuration.

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Technical Specs & Signals

Category🧮Data Science Tools
PricingFree
More technical detailsExpand â–¾
AuthNo auth required
ClientsClaude Desktop
Last updatedSep 7, 2026
9/10 checks healthy over the last 32d
Views3
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars26
GitHub Star CountTotal stargazers on GitHub representing community popularity (26 stars).
Last commit7d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 4, 2026
40Quality signal: Fair · 40/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools13/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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