Execute Python/SymPy code to perform symbolic mathematics operations including algebra, calculus, and equation solving within a secure sandbox environment.
MIT
619,939 tools. Updated 2026-09-28 21:07
"SymPy" matching MCP tools:
- Parse a string into a symbolic expression for advanced algebraic computations with SymPy.MIT
- Compute determinant, inverse, eigenvalues, transpose, rank, or trace of a numerical grid by supplying its rows as a JSON array of numbers or expressions.Apache 2.0
- Symbolically evaluate math expressions with SymPy: compute derivatives, integrals, series expansions, and closed forms from expressions like 'diff(sin(x)*x, x)'.Apache 2.0
- Convert quantities between units across metric/imperial length, mass, speed, energy, pressure, temperature, volume, data sizes, and more. Use unit aliases like mph, celsius, or gb to get exact conversions.Apache 2.0
- Parses natural-language or LaTeX PDE descriptions into a structured SymPy spec. Produces compile-checked input for downstream PDE derivation and verification.MIT
Matching MCP Servers
- AlicenseCqualityCmaintenanceAn MCP server that provides access to SymPy's symbolic mathematics library for advanced algebraic computations. It enables users to perform complex tasks such as symbolic simplification, calculus, equation solving, matrix operations, and number theory.10035 PyPIMIT
- AlicenseAqualityDmaintenanceA secure mathematical computation sandbox that enables LLMs to perform symbolic math operations like algebra, calculus, and equation solving via SymPy. It features low-latency execution through pre-warmed process pools and provides standardized JSON outputs for reliable agent integration.12MIT
- Compile verified symbolic derivations into a reusable Python function. Input verification steps, parameters, and return variables to generate executable code.Apache 2.0
- Solve ODE initial value problems using the Runge-Kutta 4 method. Input equation, x0, y0, xf, and step size to get numerical solution, exact solution, and per-step errors.MIT
- Define and store multiple symbolic variables with specific assumptions efficiently. Ideal for managing complex mathematical variables in symbolic algebra tasks.Apache 2.0
- Clear all stored variables, functions, expressions, and reset the state of the Symbolic Algebra MCP Server for the next computation, ensuring a clean workspace.Apache 2.0
- Verify that a closed-form expression matches a decimal value by independent high-precision re-evaluation, requiring at least 20 agreeing digits before accepting the identity.Apache 2.0
- Convert verified SymPy derivation steps into executable Python functions with specified parameters, descriptions, and return values.Apache 2.0
- Evaluate mathematical expressions from simple arithmetic to trigonometry and logarithms, with variable substitution for dynamic calculations.MIT
- Retrieve accurate scientific formulas from Wikidata, BioModels, and SciPy. Search by name or domain to get equations with LaTeX and SymPy representations.Apache 2.0
- Calculate symbolic summations for finite and infinite series, returning LaTeX-formatted results with convergence conditions.Apache 2.0
- Solve single inequalities to find solution sets, parameter ranges, stability conditions, or domain restrictions. Returns interval notation.Apache 2.0
- Simplify powers and exponentials by combining bases and exponents using algebraic rules, reducing expressions like x^2 * x^3 to x^5.Apache 2.0
- Transform a space or time-domain expression into its frequency-domain form. Useful for spectral analysis, signal processing, and periodic dosing evaluation.Apache 2.0
- Parse and store symbolic expressions with SymPy, assigning them to temporary or user-defined variables. Supports equations and matrices while applying canonicalization rules by default.Apache 2.0
- Define a probability distribution with PDF/PMF for modeling uncertainty, variability, error propagation, or Monte Carlo simulations. Supports continuous and discrete types.Apache 2.0
- Determines whether a mathematical expression satisfies a specific property under given assumptions. Returns True, False, or Unknown to validate domains and identify singularities.Apache 2.0