gauss-lang-mcp

# gauss-mcp [](LICENSE) [](https://www.python.org/) [](https://github.com/merwanroudane/mcp_gauss) [](https://www.aptech.com/) Drive **GAUSS** from Python, and expose it to LLM clients over the Model Context Protocol. Author: Dr Merwan Roudane Built and tested against **GAUSS 26.1.1** on Windows. ## Why this exists Aptech publishes a [reference for AI assistants](https://github.com/aptech/gauss-llm-reference) so they write better GAUSS, but writing is not running: an assistant that cannot execute the code never learns whether it worked or what the numbers were. This connects an assistant to a real GAUSS installation, so the results come from GAUSS rather than from the model. ## How it drives GAUSS Through `tgauss`, the terminal build that ships with an ordinary GAUSS installation — not the GAUSS Engine, which is richer but needs a separate licence key from Aptech. Each call is its own `tgauss` process, so nothing would normally carry over. The workspace is saved on the way out and restored on the way in, which makes a run of calls behave like one continuous session: a matrix built in one call is still there in the next. ## Install The distribution is **`gauss-lang-mcp`** on PyPI: plain `gauss-mcp` was already taken by an unrelated package about import workflows, nothing to do with the Aptech language. The import name stays `gauss_mcp`. ```bash pip install "gauss-lang-mcp[pandas]" ``` GAUSS is found automatically under `C:\gauss*` and `C:\Program Files\gauss*`. Set `GAUSS_HOME` to choose between installations. ## Library use ```python from gauss_mcp import Gauss with Gauss() as g: g.run(""" rndseed 90210; n = 400; x = rndn(n, 1); y = 1.25 + 0.8*x + 0.3*rndn(n, 1); des = ones…