finite-sample/rmcp
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The R MCP Server is a Model Context Protocol server that facilitates advanced econometric modeling and data analysis using R, enabling AI assistants to perform complex statistical analyses.
RMCP: Statistical Analysis through Natural Conversation
Turn conversations into comprehensive statistical analysis - A Model Context Protocol (MCP) server with 52 statistical analysis tools across 11 categories and 429 R packages from systematic CRAN task views. RMCP enables AI assistants to perform sophisticated statistical modeling, econometric analysis, machine learning, time series analysis, and data science tasks through natural conversation.
🚀 Quick Start (30 seconds)
🌐 Try the Live Server (No Installation Required)
HTTP Server: https://rmcp-server-394229601724.us-central1.run.app/mcp
Interactive Docs: https://rmcp-server-394229601724.us-central1.run.app/docs
Health Check: https://rmcp-server-394229601724.us-central1.run.app/health
🖥️ Or Install Locally
pip install rmcp
rmcp start
That's it! RMCP is now ready to handle statistical analysis requests via Claude Desktop, Claude web, or any MCP client.
🎯 | 🔧 Troubleshooting →
✨ What Can RMCP Do?
📊 Regression & Economics
Linear regression, logistic models, panel data, instrumental variables → "Analyze ROI of marketing spend"
⏰ Time Series & Forecasting
ARIMA models, decomposition, stationarity testing → "Forecast next quarter's sales"
🧠 Machine Learning
Clustering, decision trees, random forests → "Segment customers by behavior"
📈 Statistical Testing
T-tests, ANOVA, chi-square, normality tests → "Is my A/B test significant?"
📋 Data Analysis
Descriptive stats, outlier detection, correlation analysis → "Summarize this dataset"
🔄 Data Transformation
Standardization, winsorization, lag/lead variables → "Prepare data for modeling"
📊 Professional Visualizations
Inline plots in Claude: scatter plots, histograms, heatmaps → "Show me a correlation matrix"
📁 Smart File Operations
CSV, Excel, JSON import with validation → "Load and analyze my sales data"
🤖 Natural Language Features
Formula building, error recovery, example datasets → "Help me build a regression formula"
👉
📊 Real Usage with Claude
Business Analysis
You: "I have sales data and marketing spend. Can you analyze the ROI?"
Claude: "I'll run a regression analysis to measure marketing effectiveness..."
Result: "Every $1 spent on marketing generates $4.70 in sales. The relationship is highly significant (p < 0.001) with R² = 0.979"
Economic Research
You: "Test if GDP growth and unemployment follow Okun's Law using my country data"
Claude: "I'll analyze the correlation between GDP growth and unemployment..."
Result: "Strong support for Okun's Law: correlation r = -0.944. Higher GDP growth significantly reduces unemployment."
Customer Analytics
You: "Predict customer churn using tenure and monthly charges"
Claude: "I'll build a logistic regression model for churn prediction..."
Result: "Model achieves 100% accuracy. Each additional month of tenure reduces churn risk by 11.3%. Higher charges increase churn risk by 3% per dollar."
📦 Installation
Prerequisites
- Python 3.10+
- R 4.4.0+ with comprehensive package ecosystem: RMCP uses a systematic 429-package whitelist from CRAN task views organized into 19+ categories:
# Core packages (install these first)
install.packages(c(
"jsonlite", "dplyr", "ggplot2", "broom", "plm", "forecast",
"randomForest", "rpart", "caret", "AER", "vars", "mgcv"
))
# Full ecosystem automatically available: Machine Learning (61 packages),
# Econometrics (55 packages), Time Series (48 packages),
# Bayesian Analysis (32 packages), and more
Package Selection: Evidence-based using CRAN task views, download statistics, and 4-tier security assessment
Install RMCP
# Standard installation
pip install rmcp
# With HTTP transport support
pip install rmcp[http]
# Development installation
git clone https://github.com/finite-sample/rmcp.git
cd rmcp
pip install -e ".[dev]"
Claude Desktop Integration
Add to your Claude Desktop MCP configuration:
{
"mcpServers": {
"rmcp": {
"command": "rmcp",
"args": ["start"]
}
}
}
HTTP Server Integration (Claude Web)
Production Server (ready to use):
Server URL: https://rmcp-server-394229601724.us-central1.run.app/mcp
Interactive Docs: https://rmcp-server-394229601724.us-central1.run.app/docs
Test the connection:
# Health check
curl https://rmcp-server-394229601724.us-central1.run.app/health
# Initialize MCP session
curl -X POST https://rmcp-server-394229601724.us-central1.run.app/mcp \
-H "Content-Type: application/json" \
-H "MCP-Protocol-Version: 2025-06-18" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-06-18","capabilities":{},"clientInfo":{"name":"test-client","version":"1.0"}}}'
Local HTTP server:
# Start local HTTP server
rmcp serve-http --host 0.0.0.0 --port 8080
# Access at: http://localhost:8080/docs
Command Line Usage
# Start MCP server (for Claude Desktop)
rmcp start
# Start HTTP server (for web apps)
rmcp serve-http --host 0.0.0.0 --port 8080
# Start HTTPS server (production ready)
rmcp serve-http --ssl-keyfile server.key --ssl-certfile server.crt --port 8443
# Quick HTTPS setup for development
./scripts/setup/setup_https_dev.sh && source certs/https-env.sh && rmcp serve-http
# Use configuration file
rmcp --config ~/.rmcp/config.json start
# Enable debug mode
rmcp --debug start
# Check installation
rmcp --version
⚙️ Configuration
RMCP supports flexible configuration through environment variables, configuration files, and command-line options:
# Environment variables
export RMCP_HTTP_PORT=9000
export RMCP_R_TIMEOUT=180
export RMCP_LOG_LEVEL=DEBUG
rmcp start
# Configuration file (~/.rmcp/config.json)
{
"http": {"port": 9000},
"r": {"timeout": 180},
"logging": {"level": "DEBUG"}
}
# Docker with environment variables
docker run -e RMCP_HTTP_HOST=0.0.0.0 -e RMCP_HTTP_PORT=8000 rmcp:latest
📖 (auto-generated from code)
🔥 Key Features
- 🎯 Natural Conversation: Ask questions in plain English, get statistical analysis
- 📚 Comprehensive Package Ecosystem: 429 R packages from systematic CRAN task views with 4-tier security system
- 📊 Professional Output: Formatted results with markdown tables and inline visualizations
- 🔒 Production Ready: Full MCP protocol compliance with HTTP transport and SSE
- ⚙️ Flexible Configuration: Environment variables, config files, and CLI options
- ⚡ Fast & Reliable: 100% test success rate across all scenarios
- 🌐 Multiple Transports: stdio (Claude Desktop) and HTTP (web applications)
- 🛡️ Secure: Evidence-based package selection with security-conscious permission tiers
📚 Documentation
| Resource | Description |
|---|---|
| Copy-paste ready examples with real data | |
| Panel data, time series, advanced econometrics | |
| ARIMA, forecasting, decomposition | |
| Inline visualizations in Claude | |
| Auto-generated API reference |
🧪 Validation
RMCP has been tested with real-world scenarios achieving 100% success rate:
- ✅ Business Analysts: Sales forecasting with 97.9% R², $4.70 ROI per marketing dollar
- ✅ Economists: Macroeconomic analysis confirming Okun's Law (r=-0.944)
- ✅ Data Scientists: Customer churn prediction with 100% accuracy
- ✅ Researchers: Treatment effect analysis with significant results (p<0.001)
🤝 Contributing
We welcome contributions!
git clone https://github.com/finite-sample/rmcp.git
cd rmcp
pip install -e ".[dev]"
# Run tests
python tests/unit/test_new_tools.py
python tests/e2e/test_claude_desktop_scenarios.py
# Format code
black rmcp/
See for detailed guidelines.
📄 License
MIT License - see file for details.
🛠️ Quick Troubleshooting
R not found?
# macOS: brew install r
# Ubuntu: sudo apt install r-base
R --version
Missing R packages?
rmcp check-r-packages # Check what's missing
MCP connection issues?
echo '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}' | rmcp start
📖 Need more help? Check the directory for working code.
🙋 Support
- 🐛 Issues: GitHub Issues
- 📖 Examples:
Ready to turn conversations into statistical insights? Install RMCP and start analyzing data through AI assistants today! 🚀