Quick Start Guide

This guide will get you up and running with RMCP in minutes.

Starting the Server

Install RMCP:
```
pip install rmcp
```
Check R packages:
```
rmcp check-r-packages
```
Start the MCP server:
```
rmcp start
```

Basic Usage Examples

Linear Regression

{
    "tool": "linear_model",
    "data": {
        "x": [1, 2, 3, 4, 5],
        "y": [2, 4, 6, 8, 10]
    },
    "formula": "y ~ x"
}

Correlation Analysis

{
    "tool": "correlation_analysis",
    "data": {
        "var1": [1, 2, 3, 4, 5],
        "var2": [2, 4, 6, 8, 10],
        "var3": [1, 3, 5, 7, 9]
    }
}

Visualization with Inline Display

{
    "tool": "scatter_plot",
    "data": {
        "x": [1, 2, 3, 4, 5],
        "y": [2, 4, 6, 8, 10]
    },
    "x_var": "x",
    "y_var": "y",
    "return_image": true
}

Working with Real Data

Load Example Datasets

{
    "tool": "load_example",
    "dataset_name": "sales",
    "size": "small"
}

Import Your Data

{
    "tool": "read_csv",
    "file_path": "/path/to/your/data.csv"
}

Natural Language Formula Building

{
    "tool": "build_formula",
    "description": "predict sales from marketing spend"
}

Error Recovery

{
    "tool": "suggest_fix",
    "error_message": "object 'sales' not found",
    "tool_name": "linear_model"
}

Next Steps

../troubleshooting - Troubleshooting common issues
API Reference - Complete API reference