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    Let LLM help you achieve your regression analysis with Stata ✨ 
    Evolve from reg monkey to causal thinker 🐒 -> 🧐
News:
StataFinder, but it is not stable, please config your STATA_CLI into your environment.Finding our newest research? Click here or visit reports website.
Looking for others?
- Trace DID: If you want to fetch the newest information about DID (Difference-in-Difference), click here. Now there is a Chinese translation by Sepine Tam and StataMCP-Team 🎉
 - Jupyter Lab Usage (Important: Stata 17+) here
 - NBER-MCP & AER-MCP 🔧 under construction
 - Econometrics-Agent
 - 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. Confused it? 💡 Difference
 
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
You can open your terminal and cd to your working directory, and run:
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:
The details of agent mode find here.
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:
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 #L37 and #L68
If you want to use a Stata-Agent in another agent, here is a simple example:
import asyncio from agents import Agent, Runner from stata_mcp.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))
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.
{ "mcpServers": { "stata-mcp": { "command": "uvx", "args": [ "stata-mcp" ] } } }
For more detailed usage information, visit the Usage guide.
And some advanced usage, visit the Advanced guide
Notes:
- If you are located in China, a short uv usage document you can find here.
 - 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.
 
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.
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
pip install stata-mcp
Download source code and compile
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:
uvx /path/to/your/whl/stata_mcp-1.12.1-py3-non-any.whl # here is the wheel file name, you can change it to your version
For more information, refer to the Statement.
If you encounter any bugs or have feature requests, please open an issue.
If you use Stata-MCP in your research, please cite this repository using one of the following formats:
@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 = {1.12.1} }
Song Tan. (2025). Stata-MCP: Let LLM help you achieve your regression analysis with Stata (Version 1.12.1) [Computer software]. https://github.com/sepinetam/stata-mcp
Song Tan. 2025. "Stata-MCP: Let LLM help you achieve your regression analysis with Stata." Version 1.12.1. https://github.com/sepinetam/stata-mcp.
Email: [email protected]
Or contribute directly by submitting a Pull Request! We welcome contributions of all kinds, from bug fixes to new features.
The author sincerely thanks the Stata official team for their support and the Stata License for authorizing the test development.
The Stata referred to in this project is the commercial software Stata developed by StataCorp LLC. 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. 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.