"SciPy" matching MCP tools:

• formula_categoriesA

  nsforge-mcpB

  Discover formula categories from Wikidata, BioModels, and SciPy to narrow down formula searches by category.

  Apache 2.0

• mne_install_backendA

  MNE-MCPA

  Install the MNE-Python analysis backend on demand to enable all MNE tools without a restart. Select from ica, analysis, or full profiles.

  MIT

• formula_categoriesA

  SymKitB

  List available formula categories from local library or legacy sources like Wikidata and BioModels to organize mathematical formulas.

  Apache 2.0

• execute_codeA

  cinch-mcpA

  Execute Python or JavaScript in a secure, isolated sandbox to test code, verify calculations, or transform data, and receive stdout/stderr output.

  MIT

• formula_searchA

  nsforge-mcpB

  Retrieve accurate scientific formulas from Wikidata, BioModels, and SciPy. Search by name or domain to get equations with LaTeX and SymPy representations.

  Apache 2.0

• nonparametric_testA

  statlab-mcpA

  Perform Wilcoxon, Mann-Whitney, or Kruskal-Wallis tests on CSV/Excel/JSON data to compare paired, two-group, or multi-group samples without normality assumptions. Get p-values, effect sizes, and clear conclusions.

  MIT

• formula_searchA

  SymKitB

  Search the local formula library to retrieve accurate mathematical and physical formulas by keyword or domain.

  Apache 2.0

• formula_getA

  SymKitB

  Retrieve detailed formula information from the local library or legacy sources. Optionally load the formula into an active derivation session for step-by-step symbolic computation.

  Apache 2.0

• optimize_portfolioA

  portfolio-mcpA

  Optimize portfolio weights using Efficient Frontier analysis. Choose method to maximize Sharpe ratio, minimize volatility, or target specific return or volatility.

  MIT

• session_load_formulaA

  SymKitB

  Load a mathematical expression into the current session to enable symbolic derivation and transformation. Provide expression, optional ID, and source.

  Apache 2.0

• formula_constantsA

  nsforge-mcpB

  List physical constants from SciPy CODATA 2018, including values, units, and uncertainty. Search by keyword or filter by category such as fundamental, electromagnetic, atomic, or conversion.

  Apache 2.0

• derivation_suggest_nextA

  nsforge-mcpB

  Rank candidate formulas and operations for a mathematical derivation by relevance to the goal and current expression, returning ordered suggestions to advance the derivation.

  Apache 2.0

• mne_check_statusA

  MNE-MCPA

  Checks MNE-Python and dependency versions (scikit-learn, numpy, scipy, matplotlib) plus runtime directories to confirm the MNE-MCP environment is ready for neurophysiology data analysis.

  MIT

• create_isosurface_3dA

  serbian-data-mcpB

  Generate a 3D isosurface from scattered volumetric data to highlight regions where a scalar value lies within a specified threshold. Use for pollution concentration, isotherms, or groundwater surfaces.

  MIT

• create_volume_3dA

  serbian-data-mcpB

  Render a 3D volume from scattered scalar field samples to visualize interior distributions like pollution or temperature, with configurable opacity and iso-surfaces.

  MIT

• formula_getA

  nsforge-mcpB

  Retrieve complete formula details from Wikidata, BioModels, or SciPy by ID, including LaTeX, SymPy expressions, variable definitions, units, and source URLs.

  Apache 2.0

• correlation_matrixA

  statlab-mcpA

  Computes pairwise correlations and p-values for numeric variables from data files or inline data, with Pearson, Spearman, Kendall methods and p-value adjustment for significance testing.

  MIT

• normality_testA

  statlab-mcpA

  Check if a numeric column is normally distributed via Shapiro-Wilk or D'Agostino-Pearson tests. Outputs p-value, skew, kurtosis, and normality verdict at alpha=0.05.

  MIT

• get_column_summaryA

  eda-mcpA

  Get detailed summary statistics for any column, auto-detecting its type to compute metrics like five-number summary, outlier count, mode, or date range.

  MIT

• create_streamtube_3dA

  serbian-data-mcpB

  Generates an interactive 3D streamtube plot of vector field trajectories, encoding flow magnitude via tube diameter. Visualize wind corridors, ocean currents, or magnetic field lines from grid data.

  MIT

• trend_analysisA

  statlab-mcpA

  Detect and quantify trends in time-series data with Mann-Kendall and Theil-Sen methods. Returns trend direction, strength, and significance (tau, p, slope) from CSV, JSON, Excel, or inline data.

  MIT