claude mcp add mathmethods-mcp -- npx -y mathmethods-mcp
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
1 ★ · agmonetti/mathmethods-mcp · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 1 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository agmonetti/mathmethods-mcp;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
A Model Context Protocol server that exposes a numerical-methods core as tools an LLM agent can call directly from a chat (VS Code, Zed, Claude, opencode, etc.). It is built on top of the numerical-methods engine of the academic project modeladoYsimulacion-web (UADE); the math core is **vendored** into this repository so the server is fully self-contained. Installation and Usage 1. Run with NPX (Recommended) Runs on-demand without any global installation: Claude Code (One-liner CLI) Claude Desktop & Cursor (JSON Configuration) Add to your claude_desktop_config.json or .cursor/mcp.json: --- 2. Install Globally from NPM Ideal for instant startup without network latency on every invocation: --- 3. Run with UVX (Direct Python) Any MCP client can also run the Python package directly with Astral's uvx: Run from a checkout instead (for development) Every client config above also works with uv run --frozen --project python /server.py in place of npx -y @agmonetti/mathmethods-mcp or uvx mathmethods-mcp. Tools Root finding | Tool | What it does | | ----------------------- | --------------------------------------------------- | | root_bisection | Bisection on [a, b] (requires a sign change) | | root_newton_raphson | Newton–Raphson with numeric derivative | | root_punto_fijo | Fixed-point iteration x = g(x) | | root_aitken | Aitken Δ² acceleration of fixed point | | root_comparar | All four methods compared on the same problem | Numerical integration | Tool | What it does | | ----------------------- | --------------------------------------------------- | | integral_rectangulo | Composite midpoint rule | | integral_trapecio | Composite trapezoidal rule | | integral_simpson13 | Composite Simpson 1/3 (n even) | | integral_simpson38 | Composite Simpson 3/8 (n multiple of 3) | | integral_comparar | All four rules compared on the same integral | Differentiation | Tool | What it does | | ----------------------- | --------------------------------------------------- | | finite_differences | Forward/backward/central 1st & 2nd derivatives | ODE and interpolation | Tool | What it does | | ------------------------- | ------------------------------------------------------- | | ode_rk4 | Runge–Kutta 4 (4th order) | | ode_heun | Heun predictor–corrector (2nd order) | | ode_euler | Explicit Euler (1st order) | | interpolation_lagrange | Lagrange interpolating polynomial | Monte Carlo | Tool | What it does | | ----------------------- | ------------------------------------------------------- | | mc_hit_or_miss_1d | Hit-or-miss estimator (correct for sign-changing f) | | mc_valor_promedio_1d | Mean-value estimate of ∫ₐᵇ f(x) dx | | mc_valor_promedio_2d | Mean-value estimate of a double integral | | mc_valor_promedio_3d | Mean-value estimate of a triple integral | | mc_estadistico_1d | M×N replicated experiment with statistical analysis | | mc_convergencia_1d | Running average showing the estimate converging | Dynamic systems | Tool | What it does | | ----------------------------- | --------------------------------------------------------- | | dynamic_1d_solve | Equilibria, stability, phase portrait and time series | | dynamic_1d_equilibria | Find and classify the equilibria of x' = f(x) | | dynamic_1d_bifurcation | Equilibria vs parameter (bifurcation diagram) | | dynamic_2d_linear_solve | Linear X' = A·X + B: classification, eigenvalues, analytic solution | | dynamic_2d_nonlinear_solve | Nonlinear x' = f(x,y): equilibria, Jacobian, nullclines | | dynamic_2d_conservative_solve | Divergence-free check, Hamiltonian/energy, closed orbits | | dynamic_2d_lanchester_solve | Lanchester combat model with analytic time-to-annihilation | | dynamic_2d_nonhomogeneous_solve | Non-homogeneous X' = A·X + B(t) with time-varying forcing |