RMCP: Statistical Analysis through Natural Conversation

Turn conversations into comprehensive statistical analysis - A Model Context Protocol (MCP) server with 54 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)

MCP Endpoint: https://rmcp-server-394229601724.us-central1.run.app/mcp (bearer token required) 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.

🎯 Working examples → | 🔧 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"

👉 See working examples →

📊 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 3.11+
• 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 (57 packages),
# Bayesian Analysis (40 packages), and more

Package Selection: Evidence-based, using CRAN task views and download statistics

Install RMCP

# Standard installation
pip install rmcp

# The Streamable HTTP transport ships in the base install.
# This extra adds pandas/openpyxl for Excel data handling.
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)

RMCP serves the MCP Streamable HTTP transport at /mcp (spec 2025-11-25), compatible with Claude custom connectors and OpenAI's Responses API / ChatGPT remote MCP support. Remote deployments require a bearer token.

Production Server:

Server URL: https://rmcp-server-394229601724.us-central1.run.app/mcp

Test the connection:

# Health check
curl https://rmcp-server-394229601724.us-central1.run.app/health

# Initialize MCP session (Streamable HTTP)
curl -X POST https://rmcp-server-394229601724.us-central1.run.app/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "Authorization: Bearer $RMCP_API_KEY" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-11-25","capabilities":{},"clientInfo":{"name":"test-client","version":"1.0"}}}'

Local HTTP server:

# Localhost (no auth required)
rmcp serve-http

# Remote bind requires a bearer token (or --allow-unauthenticated)
RMCP_API_KEY=your-secret rmcp serve-http --host 0.0.0.0 --port 8080

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

Shell Completion

# zsh — add to ~/.zshrc
eval "$(_RMCP_COMPLETE=zsh_source rmcp)"

# bash — add to ~/.bashrc (requires bash 4.4+)
eval "$(_RMCP_COMPLETE=bash_source rmcp)"

# fish — write to the completions directory
_RMCP_COMPLETE=fish_source rmcp > ~/.config/fish/completions/rmcp.fish

macOS ships bash 3.2, which is too old — click prints a warning and completion does nothing. Use zsh (the macOS default) or install a newer bash.

⚙️ 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

📖 Complete Configuration Guide →

🔥 Key Features

• 🎯 Natural Conversation: Ask questions in plain English, get statistical analysis
• 📚 Comprehensive Package Ecosystem: 429 R packages from systematic CRAN task views
• 📊 Professional Output: Formatted results with markdown tables and inline visualizations
• 🔒 Production Ready: Official MCP SDK with stdio and Streamable HTTP transports, plus bearer-token auth for remote deployments
• ⚙️ Flexible Configuration: Environment variables, config files, and CLI options
• ⚡ Tested at the protocol boundary: deterministic semantic, malformed-data, security, approval, and recovery contracts run through the official MCP client
• 🌐 Multiple Transports: stdio (Claude Desktop) and HTTP (web applications)
• 🛡️ Guardrails: Package allowlist, explicit user approval for file writes, package installs and system calls, and filesystem confinement for tool-written files. These guard against mistakes, not adversaries — RMCP executes R as the invoking user, so run it as a trusted local tool rather than an untrusted multi-tenant service.

📚 Documentation

🧪 Validation

RMCP's evaluation guide defines package, contract, protocol, and model-level release gates. The deterministic E2E suite launches a real RMCP stdio process, connects with the official MCP client, and checks exact statistical identities alongside malformed data, code-like inputs, filesystem escape attempts, approval state, and recovery behavior.

uv run pytest tests/evals/test_mcp_server_evals.py

🤝 Contributing

We welcome contributions!

git clone https://github.com/finite-sample/rmcp.git
cd rmcp
pip install -e ".[dev]"

# Run tests
uv run pytest tests/

# Lint and format
uv run ruff check --fix .
uv run ruff format .

📄 License

MIT License - see LICENSE 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?

rmcp list-capabilities   # verify tools register without starting a session
rmcp --debug start       # run the server with verbose logging on stderr

📖 Need more help? Check the examples directory for working code.

🙋 Support

• 🐛 Issues: GitHub Issues
• 📖 Examples: Working examples

Ready to turn conversations into statistical insights? Install RMCP and start analyzing data through AI assistants today! 🚀