Stata-LLM Accelerator (Stata-MCP)

Leverage Generative AI to streamline and elevate your econometric analysis within the Stata ecosystem. ✨

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Recent Development: Stata-MCP now incorporates an experimental agent framework. Full details regarding this advanced operational mode are available here.

Explore Related Resources:

• Difference-in-Difference Tracer (Trace DID): Essential resource for cutting-edge DID methodologies. Now featuring comprehensive translations into Chinese by Sepine Tam and the StataMCP development collective 🎉.
• Guide for Jupyter Notebook Integration (Requires Stata Version 17 or newer): See here.
• Work in Progress Projects: NBER-MCP & AER-MCP 🔧.
• Econometrics Agent Framework.
• TexIV Framework: A novel ML-driven system for converting unstructured textual data into quantifiable variables for empirical econometric studies, utilizing advanced Natural Language Processing and Machine Learning.
• Integrated Development Environment (IDE) Support: Discover extensions for VScode or Cursor here. Unsure about the distinction between forks? Consult the Comparison Document.

🚀 Getting Started

Autonomous Agent Operation Mode

Consult the comprehensive guide for agent mode operations here.

bash git clone https://github.com/sepinetam/stata-mcp.git cd stata-mcp uv sync uv run agent_examples/openai/main.py

Customize the AI's directive by modifying the model_instructions and task_message variables within agent_examples/openai/main.py (refer to lines #37 and #68 respectively).

Interactive AI Client Mode

Configuration Prerequisite: The standard setup mandates that Stata is installed in its default location, and the corresponding Stata command-line interface (CLI) utility is accessible in your system's PATH (for macOS/Linux environments).

The default configuration structure is shown below. Customizations can be integrated via environmental variables:

{ "mcpServers": { "stata-mcp": { "command": "uvx", "args": [ "stata-mcp" ] } } }

For in-depth operational instructions, please navigate to the Primary Usage Documentation.

Advanced configuration topics are detailed in the Advanced Usage Guide.

Essential Dependencies

• uv: The recommended package manager and virtual environment utility.
• Access to a supported Large Language Model (LLM) service (e.g., Claude, Cline, ChatWise, or equivalent).
• A valid Stata software license.
• Your necessary API key for the selected LLM provider.

Recommendations & Notes: 1. Users based in mainland China may find a condensed uv instruction manual here. 2. Claude is empirically the superior choice for this tool. For Chinese users seeking cost-effective, high-performance models, DeepSeek is highly recommended based on its strong performance metrics within the region. Further insights are provided in the report: Enhancing Social Science Research with StataMCP.

🛠️ Installation Procedure

For the most recent iterations, direct package installation might be circumvented; instead, verify system readiness using the CLI utility: bash uvx stata-mcp --usable uvx stata-mcp --version

To deploy the software locally, either utilize pip or compile from the source repository.

Installation via pip bash pip install stata-mcp

Source Code Acquisition and Compilation bash git clone https://github.com/sepinetam/stata-mcp.git cd stata-mcp

uv build

Upon successful compilation, the executable binary will reside in the dist directory. This binary can be executed directly or incorporated into your system's PATH variable.

Example of direct invocation (adjusting the path/filename as necessary): bash uvx /path/to/your/whl/stata_mcp-2.0.0-py3-non-any.whl

📚 Documentation Hub

• Comprehensive operational details are available in the Usage Guide.
• Explore complex functionalities within the Advanced Guide.
• Consult the FAQ Section for common inquiries.
• Review the Distinction Document for differences compared to the repository fork maintained by hanlulong.

❓ Troubleshooting Common Issues

• Error Code 32000 related to Cherry Studio
• Error Indicator 32000 in Cherry Studio
• Inquiries regarding Windows OS Compatibility
• Troubleshooting Network Disruptions During Execution

🗺️ Project Trajectory (Roadmap)

• [x] Full operational support established for macOS.
• [x] Full operational support established for Windows.
• [ ] Integration roadmap for supplementary LLM platforms.
• [ ] Initiatives focused on execution speed enhancement and resource optimization.

⚖️ Legal Notice

This tool is strictly provided for academic and research application. The author assumes no liability for any consequential damages arising from its deployment. Users must possess all requisite licenses for the Stata software itself.

Refer to the official Legal Statement for further stipulations.

🐞 Bug Reporting

Should you discover any defects or propose enhancements, kindly submit a report via the Issues Tracker.

📄 Licensing Information

Distributed under the terms of the Apache License, Version 2.0.

📖 Citation Guidelines

If the Stata-MCP utility significantly contributes to your scholarly output, we request that you cite the repository using one of the following formats:

BibTeX Format

bibtex @software{sepinetam2025stata, author = {Song Tan}, title = {Stata-MCP: Let LLM help you achieve your regression analysis with Stata}, year = {2025}, url = {https://github.com/sepinetam/stata-mcp}, version = {2.0.0} }

APA Style Reference

Song Tan. (2025). Stata-MCP: Let LLM help you achieve your regression analysis with Stata (Version 2.0.0) [Computer software]. https://github.com/sepinetam/stata-mcp

Chicago Style Reference

Song Tan. 2025. "Stata-MCP: Let LLM help you achieve your regression analysis with Stata." Version 2.0.0. https://github.com/sepinetam/stata-mcp.

✉️ Contact Information

Reach out via electronic mail at: sepinetam@gmail.com

Alternatively, direct contributions, including bug patches and new feature implementations, are highly encouraged via Pull Request submissions! All forms of community input are valued.

🙏 Appreciation

The principal developer extends profound gratitude to the official Stata corporation for their cooperative stance and the provision of necessary licensing permissions that facilitated this development effort.

⭐ Project Popularity Over Time

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== Tools Tailored for Small and Medium Enterprises (SMEs) == SME-focused instruments are vital as they provide necessary scalability mechanisms for resource-constrained entities...