io.github.clouatre-labs/math-mcp-learning-server · v0.12.5 · finance-and-payments
Math MCP Learning is healthy: it completed an MCP handshake in 4665 ms and exposes 17 tools.
Educational MCP server with 17 math/stats tools, visualizations, and persistent workspace
Endpoint: https://math-mcp.fastmcp.app/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 17 |
| Latency | 4665 ms |
| Last checked (UTC) | 2026-10-15T03:15:47.638Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-15T03:15:47.638Z | Healthy | 4665 |
calc_expression | Safely evaluate mathematical expressions with support for basic operations and math functions. Supported operations: +, -, *, /, **, () Supported functions: sin, cos, tan, log, sqrt, abs, pow |
calc_statistics | Perform statistical calculations on a list of numbers. Available operations: mean, median, mode, std_dev, variance |
calc_interest | Calculate compound interest for investments. Formula: A = P(1 + r/n)^(nt) Where: - P = principal amount - r = annual interest rate (as decimal) - n = number of times interest compounds per year - t = time in years |
calc_units | Convert between different units of measurement. Supported unit types: - length: mm, cm, m, km, in, ft, yd, mi - weight: g, kg, oz, lb - temperature: c, f, k (Celsius, Fahrenheit, Kelvin) |
matrix_multiply | Multiply two matrices (A × B). |
matrix_transpose | Transpose a matrix (swap rows and columns). |
matrix_determinant | Calculate the determinant of a square matrix. |
matrix_inverse | Calculate the inverse of a square matrix. |
matrix_eigenvalues | Calculate the eigenvalues of a square matrix. |
workspace_save | Save calculation to persistent workspace (survives restarts). |
workspace_load | Load previously saved calculation result from workspace. |
plot_function | Generate mathematical function plots (requires matplotlib). |
plot_histogram | Create statistical histograms (requires matplotlib). |
plot_line_chart | Create a line chart from data points (requires matplotlib). |
plot_scatter | Create a scatter plot from data points (requires matplotlib). |
plot_box_plot | Create a box plot for comparing distributions (requires matplotlib). |
plot_financial_line | Generate and plot synthetic financial price data (requires matplotlib). Creates realistic price movement patterns for educational purposes. Does not use real market data. |