stata-mcp

<h1 align="center"> <a href="https://www.statamcp.com"> <img src="https://example-data.statamcp.com/logo_with_name.jpg" alt="logo" width="300"/> </a> </h1> <h1 align="center">Stata-MCP</h1> <p align="center"> Let LLM help you achieve your regression analysis with Stata ✨ <br> Evolve from reg monkey to causal thinker 🐒 -> 🧐 </p> [](README.md) [](source/docs/README/cn/README.md) [](source/docs/README/fr/README.md) [](source/docs/README/sp/README.md) [](https://pypi.org/project/stata-mcp/) [](https://pepy.tech/projects/stata-mcp) [](LICENSE) [](https://github.com/sepinetam/stata-mcp/issues/new) [](https://deepwiki.com/SepineTam/stata-mcp) --- **News**: - Use Stata-MCP in Claude Code, look [here](#use-stata-mcp-in-claude-code) - Try to use agent mode as tool? Now it is supported more easily [here](source/docs/Usages/agent_as/agent_as_tool.md). - Want to evaluate your LLM? Look [here](source/docs/Usages/Evaluation.md). - Update `StataFinder`, but it is not stable, please config your `STATA_CLI` into your environment. Finding our **newest research**? Click [here](source/reports/README.md) or visit [reports website](https://www.statamcp.com/reports). > Looking for others? > > - [STOP Dataset](https://opendata.ai4cssci.com): StataMCP-Team Opendata Project 📊, we have open-sourced a comprehensive dataset collection for social science research, aiming to enable the future of AI-driven and data-powered research paradigms. > - [Trace DID](https://github.com/asjadnaqvi/DiD): If you want to fetch the newest information about DID (Difference-in-Difference), click [here](https://asjadnaqvi.github.io/DiD/). Now there is a Chinese translation by [Sepine Tam](https://github.com/sepine) and [StataMCP-Team](https://github.com/statamcp-team) 🎉 > - Jupyter Lab Usage (Important: Stata 17+) [here](source/docs/JupyterStata.md) > - [NBER-MCP](https://github.com/sepinetam/NBER-MCP) & [AER-MCP](https://github.com/sepinetam/AER-MCP) 🔧 under construction > - [Econometrics-Agent](https://github.com/FromCSUZhou/Econometrics-Agent) > - [TexIV](https://github.com/sepinetam/TexIV): A machine learning-driven framework that transforms text data into usable variables for empirical research using advanced NLP and ML techniques > - A VScode or Cursor integrated [here](https://github.com/hanlulong/stata-mcp). Confused it? 💡 [Difference](source/docs/Difference.md) ## 💡 Quick Start ### Use Stata-MCP in Claude Code We can use Stata-MCP in Claude Code as its prefect agentic ability. Before using it, please make sure you have ever install `Claude Code`, if you don't know how to install it, visit on [GitHub](https://github.com/anthropics/claude-code) You can open your terminal and `cd` to your working directory, and run: ```bash claude mcp add stata-mcp --env STATA_MCP_CWD=$(pwd) -- uvx stata-mcp ``` I am not sure whether it works on Windows, as I do not have a Windows device for test it. Then, you can use Stata-MCP in Claude Code. Here are some scenarios for using it: - **Paper Replication**: Replicate empirical studies from economics papers - **Quick Hypothesis Testing**: Validate economic hypotheses through regression analysis - **Stata Learning Assistant**: Learn econometrics with step-by-step Stata explanations - **Code Organization**: Review and optimize existing Stata do-files - **Result Interpretation**: Understand complex statistical outputs and regression results ### Agent Mode The details of agent mode find [here](source/agent_examples/README.md). ```bash git clone https://github.com/sepinetam/stata-mcp.git cd stata-mcp uv sync uv pip install -e . stata-mcp --version # for test whether stata-mcp is installed successfully. stata-mcp --agent # now you have enjoy your stata-mcp agent mode. ``` or you can directly use it with `uvx`: ```bash uvx stata-mcp --version # for test whether it could be used on your computer. uvx stata-mcp --agent ``` You can edit the task in `agent_examples/openai/main.py` for variable `model_instructions` and `task_message`, [click me](source/agent_examples/openai/main.py) #L37 and #L68 ### Agent as Tool If you want to use a Stata-Agent in another agent, [here](source/docs/Usages/agent_as/agent_as_tool.md) is a simple example: ```python import asyncio from agents import Agent, Runner from stata_mcp.agent_as.agent_as_tool import StataAgent # init stata agent and set as tool stata_agent = StataAgent() sa_tool = stata_agent.as_tool() # Create main Agent agent = Agent( name="Assistant", instructions="You are a helpful assistant", tools=[sa_tool], ) # Then run the agent as usual. async def main(task: str, max_turns: int = 30): result = await Runner.run(agent, input=task, max_turns=max_turns) return result if __name__ == "__main__": econ_task = "Use Stata default data to find out the relationship between mpg and price." asyncio.run(main(econ_task)) ``` ### AI Chat-Bot Client Mode > Standard config requires: please make sure the stata is installed at the default path, and the stata cli (for macOS and Linux) exists. The standard config json as follows, you can DIY your config via add envs. ```json { "mcpServers": { "stata-mcp": { "command": "uvx", "args": [ "stata-mcp" ] } } } ``` For more detailed usage information, visit the [Usage guide](source/docs/Usages/Usage.md). And some advanced usage, visit the [Advanced guide](source/docs/Usages/Advanced.md) ### Prerequisites - [uv](https://github.com/astral-sh/uv) - Package installer and virtual environment manager - Claude, Cline, ChatWise, or other LLM service - Stata License - Your API-KEY from LLM > Notes: > 1. If you are located in China, a short uv usage document you can find [here](source/docs/ChinaUsers/uv.md). > 2. Claude is the best choice for Stata-MCP, for Chinese, I recommend to use DeepSeek as your model provider as it is cheap and powerful, also the score is highest in China provider, if you are increased in it, visit the report [How to use StataMCP improve your social science research](https://statamcp.com/reports/2025/09/21/stata_mcp_a_research_report_on_ai_assisted_empirical_research). ### Installation For the new version, you don't need to install the `stata-mcp` package again, you can just use the following command to check whether your computer can use stata-mcp. ```bash uvx stata-mcp --usable uvx stata-mcp --version ``` If you want to use it locally, you can install it via pip or download the source code. **Download via pip** ```bash pip install stata-mcp ``` **Download source code and compile** ```bash git clone https://github.com/sepinetam/stata-mcp.git cd stata-mcp uv build ``` Then you can find the compiled `stata-mcp` binary in the `dist` directory. You can use it directly or add it to your PATH. For example: ```bash uvx /path/to/your/whl/stata_mcp-1.13.0-py3-non-any.whl # here is the wheel file name, you can change it to your version ``` ## 📝 Documentation - For more detailed usage information, visit the [Usage guide](source/docs/Usages/Usage.md). - Advanced Usage, visit the [Advanced](source/docs/Usages/Advanced.md) - Some questions, visit the [Questions](source/docs/Usages/Questions.md) - Difference with [Stata-MCP@hanlulong](https://github.com/hanlulong/stata-mcp), visit the [Difference](source/docs/Difference.md) ## 💡 Questions - [Cherry Studio 32000 wrong](source/docs/Usages/Questions.md#cherry-studio-32000-wrong) - [Cherry Studio 32000 error](source/docs/Usages/Questions.md#cherry-studio-32000-error) - [Windows Support](source/docs/Usages/Questions.md#windows-supports) - [Network Errors When Running Stata-MCP](source/docs/Usages/Questions.md#network-errors-when-running-stata-mcp) ## 🚀 Roadmap - [x] macOS support - [x] Windows support - [ ] Additional LLM integrations (With a new webUI) - [ ] Performance optimizations (Via prompt and context engineering) For more information, refer to the [Statement](source/docs/Rights/Statement.md). ## 🐛 Report Issues If you encounter any bugs or have feature requests, please [open an issue](https://github.com/sepinetam/stata-mcp/issues/new). ## 📄 License [Apache License 2.0](LICENSE) ## 📚 Citation If you use Stata-MCP in your research, please cite this repository using one of the following formats: ### BibTeX ```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 = {1.13.0} } ``` ### APA ``` Song Tan. (2025). Stata-MCP: Let LLM help you achieve your regression analysis with Stata (Version 1.13.0) [Computer software]. https://github.com/sepinetam/stata-mcp ``` ### Chicago ``` Song Tan. 2025. "Stata-MCP: Let LLM help you achieve your regression analysis with Stata." Version 1.13.0. https://github.com/sepinetam/stata-mcp. ``` ## 📬 Contact Email: [sepinetam@gmail.com](mailto:sepinetam@gmail.com) Or contribute directly by submitting a [Pull Request](https://github.com/sepinetam/stata-mcp/pulls)! We welcome contributions of all kinds, from bug fixes to new features. ## ❤️ Acknowledgements The author sincerely thanks the Stata official team for their support and the Stata License for authorizing the test development. ## 📃 Statement The Stata referred to in this project is the commercial software Stata developed by [StataCorp LLC](https://www.stata.com/company/). This project is not affiliated with, endorsed by, or sponsored by StataCorp LLC. This project does not include the Stata software or any installation packages; users must obtain and install a validly licensed copy of Stata from StataCorp. This project is licensed under [Apache-2.0](LICENSE). The project maintainers accept no liability for any loss or damage arising from the use of this project or from actions related to Stata. More information: refer to the Chinese version at [source/docs/README/cn/README.md]; in case of any conflict, the Chinese version shall prevail. ## ✨ Star History [](https://www.star-history.com/#sepinetam/stata-mcp&Date)