High-performance MCP server for mathematical operations using Polars and scientific Python
High-performance MCP server for mathematical operations using Polars and scientific Python
A high-performance Model Context Protocol (MCP) server for math-ing whilst vibing with LLMs. Built with Polars, Pandas, NumPy, SciPy, and SymPy for optimal calculation speed and comprehensive mathematical capabilities from basic arithmetic to advanced calculus and linear algebra.
full — Complete response with all metadata (default)compact — Remove null fields, minimize whitespaceminimal — Primary value(s) only, strip metadatavalue — Normalized {value: X} structurefinal — For sequential chains, return only terminal resultcalculate — Evaluate mathematical expressions with variable substitutionpercentage — Percentage calculations (of, increase, decrease, change)round — Advanced rounding (round, floor, ceil, trunc)convert_units — Unit conversions (degrees � radians)array_operations — Element-wise operations (add, subtract, multiply, divide, power)array_statistics — Statistical measures (mean, median, std, min, max, sum)array_aggregate — Aggregations (sumproduct, weighted average, dot product)array_transform — Transformations (normalise, standardise, scale, log)Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| calculate | Evaluate mathematical expressions with variable substitution |
| percentage | Percentage calculations (of, increase, decrease, change) |
| round | Advanced rounding (round, floor, ceil, trunc) |
| convert_units | Unit conversions (degrees � radians) |
| array_operations | Element-wise operations (add, subtract, multiply, divide, power) |
| array_statistics | Statistical measures (mean, median, std, min, max, sum) |
| array_aggregate | Aggregations (sumproduct, weighted average, dot product) |
| array_transform | Transformations (normalise, standardise, scale, log) |
| statistics | Comprehensive analysis (describe, quartiles, outliers) |
| pivot_table | Create pivot tables with aggregation |
| correlation | Correlation matrices (Pearson, Spearman) |
| financial_calcs | Time value of money (PV, FV, PMT, IRR, NPV) |
| compound_interest | Compound interest with various frequencies |
| matrix_operations | Matrix operations (multiply, inverse, transpose, determinant, trace) |
| solve_linear_system | Solve Ax = b systems |
| matrix_decomposition | Decompositions (eigen, SVD, QR, Cholesky, LU) |
| derivative | Symbolic and numerical differentiation |
| integral | Symbolic and numerical integration |
| limits_series | Limits and series expansions |
{
"mcpServers": {
"Math": {
"command": "uvx",
"args": [
"vibe-math-mcp"
]
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
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