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MCP Machine Learning Agent

MCP Machine Learning Agent

Related Servers

Alternatives to MCP Machine Learning Agent

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    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables users to train and evaluate Logistic Regression and KNN models for breast cancer diagnosis, generate predictions and SHAP explanations, select the best-performing model, and export Parquet audit logs through MCP tools.
      GPL 3.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables users to train and compare breast-cancer classification models, obtain sample inputs, make predictions with Logistic Regression or KNN, evaluate metrics, select the best model, generate SHAP explanations, and export Parquet audit logs through MCP tools.
      GPL 3.0
    • A
      license
      A
      quality
      C
      maintenance
      Enables training, predicting, evaluating, and explaining Logistic Regression and KNN models for breast cancer classification through MCP tools. It also supports model selection, SHAP explanations, and Parquet audit exports.
      8
      GPL 3.0
    • A
      license
      A
      quality
      B
      maintenance
      Provides machine learning tools for training, predicting, evaluating, and auditing Logistic Regression and K-Nearest Neighbors models. A custom predict_both tool returns both models' predictions for a patient, indicates whether they agree, and records the execution for auditing.
      9
      GPL 3.0
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables local offline machine learning workflows, including CSV profiling and cleaning, classifier and neural network training, hyperparameter optimization, evaluation metrics, confusion matrix plots, Streamlit dashboards, and HTML reports through MCP tools.
      13 npm
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Local-first MCP server for credit risk analysis. It enables explainable rule discovery, statistical validation, PSI drift monitoring, and root-cause diagnosis on user-approved Parquet data while preserving privacy.
      -