#Data Science MCP Servers

Manage data science via Dataiku. List projects and datasets, track pipeline jobs, run automation scenarios, and monitor ML models directly from any AI agent.

Manage ML lifecycle via MLflow. Track training runs, monitor metrics, and audit the model registry.

Manage machine learning experiments via Comet. Track model metrics, audit project workspaces, and inspect ML run parameters directly from any AI agent.

Manage AutoML via DataRobot. Monitor projects and models, track deployments, and audit ML datasets directly from any AI agent.

Manage collaborative data analysis via Mode Analytics. List spaces, query reports, and trigger report runs directly from any AI agent.

Manage ML experiments via Neptune.ai. Track training runs, monitor metrics, and audit model versions.

Perform exact linear algebra. Multiply, transpose, invert, and compute determinants of massive matrices local. Zero LLM math hallucinations.

Run exact Student's, Welch's, and Paired t-tests local. Get CPU-guaranteed p-values instead of LLM-hallucinated guesses.

Compute exact Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) for regression models. Stop hallucinating model validation metrics.

Compute the exact Area Under the ROC Curve for binary classification predictions. Local, mathematically perfect, zero LLM estimation.

Test whether your data is normally distributed using Skewness and Kurtosis analysis local. Essential pre-check before running parametric statistical tests.

Compute exact Autocorrelation (ACF) to find seasonality lags in time-series data without hallucination.

Run exact Chi-Square independence tests on contingency tables local. Get CPU-guaranteed chi² statistics and p-values for categorical analysis.

Deterministically calculate True Positives, FP, Precision, Recall, F1-Score, and Accuracy local. Stop LLM hallucinations when evaluating model metrics.

Balance skewed datasets instantly by generating mathematically sound synthetic minority data points via KNN.