advanced-math-mcp

advanced-math-mcp — MCP server for linear algebra, calculus, and symbolic math. 17 tools with a unified evaluate() expression engine. Supports matrices, eigenvalues, SVD, integrals, limits, derivatives, and more.

MCP (Model Context Protocol) server for advanced mathematics — linear algebra, vector math, symbolic computation, and calculus. Designed for use with Claude and other MCP-compatible LLMs.

Then add to your MCP client configuration (e.g.,mcp_settings.json):

{ "mcpServers": { "advanced-math-mcp": { "command": "advanced-math-mcp", "args": [], "alwaysAllow": [ "evaluate", "set_variable", "get_variable", "list_variables", "clear_variables", "matrix_create", "matrix_identity", "matrix_zeros", "matrix_diagonal", "symbolic_simplify", "symbolic_substitute", "symbolic_derivative", "symbolic_expand", "symbolic_integrate", "symbolic_definite_integral", "symbolic_limit", "symbolic_partial_derivative" ] } } }

All matrix/vector operations use a singleevaluatetool with natural expression syntax:

// Arithmetic evaluate("A + B") // addition evaluate("A - B") // subtraction evaluate("A  B") // matrix multiplication evaluate("A ^ 3") // matrix power // Properties evaluate("det(A)") // determinant evaluate("trace(A)") // trace evaluate("rank(A)") // rank evaluate("inv(A)") // inverse evaluate("transpose(A)") // transpose // Decompositions evaluate("eig(A)") // eigenvalues & eigenvectors evaluate("charpoly(A)") // characteristic polynomial (2×2, 3×3) evaluate("lu(A)") // LU decomposition evaluate("qr(A)") // QR decomposition evaluate("svd(A)") // singular value decomposition // Linear systems evaluate("solve(A, b)") // solve Ax = b

evaluate("dot([1,2,3], [4,5,6])") // dot product → 32 evaluate("cross([1,2,3], [4,5,6])") // cross product → [-3, 6, -3] evaluate("norm([3,4])") // L2 norm → 5 evaluate("norm([3,4], \"1\")") // L1 norm → 7 evaluate("project([3,4], [1,0])") // vector projection → [3, 0]

evaluate("[[1,2],[3,4]]  [[5,6],[7,8]]") // → [[19,22],[43,50]] evaluate("det([[4,1],[2,3]])") // → 10 evaluate("inv([[4,7],[2,6]])") // → [[0.6,-0.7],[-0.2,0.4]]

set_variable("A", "[[1,2],[3,4]]") set_variable("B", "[[5,6],[7,8]]") evaluate("A  B") // uses stored variables list_variables() // see all defined variables clear_variables() // reset

symbolic_simplify("x^2 + 2x + 1 - (x+1)^2") // → 0 symbolic_expand("(x+1)(x-1)(x+2)") // → x^3 + 2x^2 - x - 2

// Single variable symbolic_substitute("x^2 + 2x", { x: "3" }) // → 15 // Multi-variable symbolic_substitute("x^2 + yx + z", { x: "3", y: "2", z: "1" }) // → 16

// Derivatives symbolic_derivative("x^3 + 2x^2", "x") // → 3x^2 + 4x symbolic_partial_derivative("x^2y + sin(z)", "x", 2) // → 2y (second partial) // Integration symbolic_integrate("x^2 + sin(x)", "x") // → 0.333x^3 - cos(x) + C symbolic_definite_integral("x^2", "x", "0", "2") // → 2.667 (∫₀² x² dx) // Limits symbolic_limit("sin(x)/x", "x", "0") // → 1

src/ ├── index.ts # Entry point, loads nerdamer plugins ├── server.ts # MCP server setup, tool routing ├── types.ts # Shared types and Zod schemas ├── engine/ │ ├── evaluator.ts # Unified expression evaluator (mathjs + custom functions) │ ├── symbolic.ts # Symbolic engine (nerdamer + mathjs) │ ├── math-engine.ts # Low-level matrix operations │ └── format.ts # Output formatting utilities └── tools/ ├── evaluate.ts # evaluate + variable management tools ├── matrix-create.ts # matrix_create, identity, zeros, diagonal ├── symbolic.ts # symbolic_simplify, substitute, derivative, expand └── calculus.ts # symbolic_integrate, definite_integral, limit, partial_derivative

The evaluator extends mathjs with these custom functions:

git clone https://github.com/PsyWhat/advanced-math-mcp.git cd advanced-math-mcp npm install npm run build # compile TypeScript npm run dev # watch mode npm link # install globally for local testing

npm test # run all tests (vitest) npm run test:watch # watch mode npm run typecheck # TypeScript validation only

- SVD: The rank-deficient SVD gives zero vectors for nullspace columns (computed via AᵀA eigen-decomposition, not full Golub-Reinsch)
- Cholesky: Not available in mathjs v13; uselu()for general decomposition
- norm(v, inf): Must use quoted"inf"(not bareinf) due to mathjs parsing
- charpoly: Numeric only, supports 2×2 and 3×3 matrices
- symbolic_limit: Some advanced limits (e.g.,(1+1/x)^xasx→∞) may not fully resolve

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