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agmonetti/mathmethods-mcp

agmonetti/mathmethods-mcp

MCP server for numerical methods and dynamic systems: root finding, integration, ODEs, Monte Carlo, 1D/2D dynamical systems, and combat models.
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Config template (adjust for your client)
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.
Third-party quality signals

Mathematical/Numerical Methods - MCP Server

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

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 |
Source
awesome · https://github.com/agmonetti/mathmethods-mcp
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