R Econometrics MCP Server

R Econometrics MCP Server

A Model Context Protocol (MCP) server that provides econometric modeling capabilities through R. This server enables AI assistants to perform sophisticated econometric analyses, including linear regression, panel data models, instrumental variables regression, and diagnostic tests.

Features

• Linear Regression: Run linear models with optional robust standard errors
• Panel Data Analysis: Fixed effects, random effects, pooling, between, and first-difference models
• Instrumental Variables: Estimate IV regression models
• Diagnostic Tests: Heteroskedasticity, autocorrelation, and functional form tests
• Resources: Reference documentation for econometric techniques
• Prompts: Pre-defined prompt templates for common econometric analyses

Installation

Prerequisites

• Python 3.8+
• R 4.0+
• R packages: plm, lmtest, sandwich, AER, jsonlite

Using Docker (Recommended)

1. Build the Docker image:
   docker build -t r-econometrics-mcp .
2. Run the container:
   docker run -it r-econometrics-mcp

Manual Installation

1. Install the required Python packages:
   pip install -r requirements.txt
2. Install the required R packages:
   install.packages(c("plm", "lmtest", "sandwich", "AER", "jsonlite"))
3. Run the server:
   python r_econometrics_mcp.py

Usage with Claude Desktop

1. Launch Claude Desktop
2. Open the MCP Servers panel
3. Add a new server with the following configuration:
   • Name: R Econometrics
   • Transport: stdio
   • Command: path/to/python r_econometrics_mcp.py
   • (Or if using Docker): docker run -i r-econometrics-mcp

Example Queries

Here are some example queries you can use with Claude once the server is connected:

Linear Regression

Panel Data Analysis

Instrumental Variables

Diagnostic Tests

Tools Reference

linear_model

Run a linear regression model.

Parameters:

• formula (string): The regression formula (e.g., 'y ~ x1 + x2')
• data (object): Dataset as a dictionary/JSON object
• robust (boolean, optional): Whether to use robust standard errors

panel_model

Run a panel data model.

Parameters:

• formula (string): The regression formula (e.g., 'y ~ x1 + x2')
• data (object): Dataset as a dictionary/JSON object
• index (array): Panel index variables (e.g., ['individual', 'time'])
• effect (string, optional): Type of effects: 'individual', 'time', or 'twoways'
• model (string, optional): Model type: 'within', 'random', 'pooling', 'between', or 'fd'

diagnostics

Perform model diagnostics.

Parameters:

• formula (string): The regression formula (e.g., 'y ~ x1 + x2')
• data (object): Dataset as a dictionary/JSON object
• tests (array): Tests to run (e.g., ['bp', 'reset', 'dw'])

iv_regression

Estimate instrumental variables regression.

Parameters:

• formula (string): The regression formula (e.g., 'y ~ x1 + x2 | z1 + z2')
• data (object): Dataset as a dictionary/JSON object

Resources

• econometrics:formulas: Information about common econometric model formulations
• econometrics:diagnostics: Reference for diagnostic tests
• econometrics:panel_data: Guide to panel data analysis in R

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License

Acknowledgments

• The R Project and R Core Team
• Developers of the plm, lmtest, sandwich, and AER packages
• Anthropic for the Model Context Protocol