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.
Add two integers together. Parameters: a (int), b (int)
Multiply two matrices. Parameters: matrix_a (List[List[float]]), matrix_b (List[List[float]])
Compute eigenvalues and eigenvectors of a square matrix. Parameters: matrix (List[List[float]])
Calculate basic statistics for a dataset including mean, median, standard deviation, minimum value, and maximum value. Parameters: data (List[float])
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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