Symbolic Algebra MCP Server

by sdiehl

pdsolve_pde

Solves partial differential equations (PDEs) using symbolic computation. Input the expression key and function name to generate a LaTeX-formatted solution for the specified PDE.

Instructions

Solves a partial differential equation using SymPy's pdsolve function.

Args: expr_key: The key of the expression (previously introduced) containing the PDE. If the expression is not an equation (Eq), it will be interpreted as PDE = 0. func_name: The name of the function (previously introduced) to solve for. This should be a function of multiple variables. Example: # First introduce variables and a function intro("x", [Assumption.REAL], []) intro("y", [Assumption.REAL], []) introduce_function("f") # Create a PDE: 1 + 2*(ux/u) + 3*(uy/u) = 0 expr_key = introduce_expression( "Eq(1 + 2*Derivative(f(x, y), x)/f(x, y) + 3*Derivative(f(x, y), y)/f(x, y), 0)" ) # Solve the PDE result = pdsolve_pde(expr_key, "f") # Returns solution with exponential terms and arbitrary function Returns: A LaTeX string representing the solution. Returns an error message string if issues occur.

Input Schema

NameRequiredDescriptionDefault
expr_keyYes
func_nameYes
hintNo

Input Schema (JSON Schema)

{ "$defs": { "PDEHint": { "enum": [ "1st_linear_constant_coeff_homogeneous", "1st_linear_constant_coeff", "1st_linear_constant_coeff_Integral", "1st_linear_variable_coeff" ], "title": "PDEHint", "type": "string" } }, "properties": { "expr_key": { "title": "Expr Key", "type": "string" }, "func_name": { "title": "Func Name", "type": "string" }, "hint": { "anyOf": [ { "$ref": "#/$defs/PDEHint" }, { "type": "null" } ], "default": null } }, "required": [ "expr_key", "func_name" ], "title": "pdsolve_pdeArguments", "type": "object" }

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