saidsurucu/rlang-mcp-python

部署与 DevOps

本页由 AI 翻译，技术细节请以原文为准。查看原文

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Repository Install

用于运行R语言的MCP服务器

概览

一个安全的基于 Docker 的模型上下文协议（MCP）服务器，用于 R 数据可视化和分析，使用 Python 和 FastMCP 构建。该工具允许您通过自然语言对话与 Claude 等大型语言模型进行统计分析。所有 R 代码均在安全的 Docker 容器中执行，确保完全隔离和安全。 - 🗣️ ：与 AI 聊天进行复杂统计分析 - 🐳 ：所有 R 代码运行在隔离容器中，网络被禁用 - 📊 ： AI 运行 R 代码并返回结果，无需你编写代码 - 📁 ：挂载多个本地目录供 R 访问 - 📈 ：自动返回为 base64 PNG 图像的图 - 🔒 ：可选自动编辑个人数据，避免进入 LLM - 💾 ： R 变量在调用间持续存在 - ⚡ ：可配置结果缓存以实现即时重复操作 - 📦 ：自动安装缺少的 R 包该项目灵感来自gdbelvin的rlang-mcp-server，但实际上是基于......

概述（AI 翻译）

一个安全的基于 Docker 的模型上下文协议（MCP）服务器，用于 R 数据可视化和分析，使用 Python 和 FastMCP 构建。

这是什么？ 该工具允许您通过自然语言对话（如 Claude）进行 R 语言分析，如 LLM 模型。所有 R 代码均在安全的 Docker 容器中执行，确保完全隔离和安全。

主要优势：

🗣️ 自然语言界面：与AI聊天进行复杂统计分析
🐳 安全Docker执行：所有R代码运行在隔离容器中，网络被禁用
📊 自动R执行：AI运行R代码并返回结果，无需你编写代码
📁 多目录挂载：挂载多个本地目录供R访问
📈 内联绘图捕捉：图表自动返回为base64 PNG图像
🔒 个人信息保护：个人数据在到达LLM前的可选自动编辑
💾 会话持久性：R个变量在调用之间保持
⚡ 智能缓存：可配置的结果缓存，支持即时重复操作
📦 自动库检测：自动安装缺失的R包

🌐 土耳其语 |英语*

概述

本页由 AI 翻译，技术细节请以原文为准。

README

以下为原文 README 节选，完整内容请查看原文。

Python R-Server MCP

A secure, Docker-based Model Context Protocol (MCP) server for R data visualization and analysis, built with Python and FastMCP.

What is this? This tool allows you to perform statistical analysis in R through natural language conversations with LLM models like Claude. All R code is executed in secure Docker containers, ensuring complete isolation and security.

Key Benefits:

🗣️ Natural Language Interface: Chat with AI to perform complex statistical analyses
🐳 Secure Docker Execution: All R code runs in isolated containers with network disabled
📊 Automatic R Execution: AI runs R code and returns results without you writing code
📁 Multiple Directory Mounting: Mount multiple local directories for R to access
📈 Inline Plot Capture: Plots automatically returned as base64 PNG images
🔒 PII Protection: Optional auto-redaction of personal data before it reaches the LLM
💾 Session Persistence: R variables persist between calls
⚡ Smart Caching: Configurable result caching for instant repeated operations
📦 Auto Library Detection: Missing R packages automatically installed

🌐 Türkçe | English

Overview

This project is inspired by gdbelvin’s rlang-mcp-server but is a complete Python reimplementation using the FastMCP framework. While the original Go version provided basic R visualization tools, this Python version extends the functionality with comprehensive security, file management, and data privacy features.

Features

🎨 Visualization & Analysis

ggplot2 Rendering: Execute R code with ggplot2 commands and return publication-ready visualizations
Inline Plot Capture: Plots automatically detected and returned as base64 PNG
R Script Execution: Run any R script with smart file handling and return formatted output
Session Persistence: R variables and workspace persist between calls via .RData

📁 File Management

Multiple Directory Mounting: Mount multiple local directories with custom mount points
Smart File Discovery: Use R scripts to explore and analyze files in mounted directories
Unmount Support: Cleanly unmount directories when done

📦 Package Management

Auto Library Detection: library() and require() calls parsed, missing packages auto-installed
Package Installation: Install R packages on-demand with version control
Automatic Dependencies: Smart package dependency resolution
Temporary Network: Network temporarily enabled only during package installation

🛡️ Security & Isolation

Mandatory Docker: All R code execution in isolated containers
Network Disabled by Default: Container cannot access internet during R execution
Resource Limits: Configurable memory (default 2GB) and CPU limits

在 GitHub 查看完整 README

安装

uvx --from git+https://github.com/saidsurucu/rlang-mcp-python rlang-mcp-python

新手？先看 mcpskill.org 教程 →

配置

{
  "mcpServers": {
    "r-server-python": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/saidsurucu/rlang-mcp-python",
        "rlang-mcp-python"
      ]
    }
  }
}