NumPy
Summary
This MCP server implementation provides NumPy-based mathematical operations and statistical analysis tools. It offers functions for matrix multiplication, eigendecomposition, polynomial fitting, and basic statistical measures. Developed using FastMCP, it's designed for AI assistants requiring advanced numerical computations, data analysis, and linear algebra operations in Python environments.
Available Actions(5)
add
Add two integers together. Parameters: a (int), b (int)
matrix_multiply
Multiply two matrices. Parameters: matrix_a (List[List[float]]), matrix_b (List[List[float]])
eigen_decomposition
Compute eigenvalues and eigenvectors of a square matrix. Parameters: matrix (List[List[float]])
statistical_analysis
Calculate basic statistics for a dataset including mean, median, standard deviation, minimum value, and maximum value. Parameters: data (List[float])
polynomial_fit
Fit a polynomial of specified degree to the given data points. Parameters: x (List[float]), y (List[float]), degree (int, default is 2)
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