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Numora Matrix Eigenvectors API
x402
Numora Matrix Eigenvectors API is a paid API for AI agents from numomo.vercel.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-14).
Computes the eigenvalues and eigenvectors of a given square matrix using pure numerical methods.
Price / call$0.1
Success—
StatusUnknown
How this service works
100 pure math computation endpoints for AI agents. Statistics, financial math, linear algebra, equation solving, calculus, number theory, sequence generation, and unit conversions. Zero external dependencies. x402 micropayments on Base.
Output
Returns a JSON object with 'success' (boolean), 'result' (an object containing arrays of eigenvalues and corresponding eigenvectors of the input matrix), and 'computation' (a human-readable string describing what was computed). Eigenvalues may be real or complex depending on the input matrix.
Example use cases
Principal Component Analysis basis
“I need the eigenvectors of my covariance matrix [[2.5, 2.4], [2.4, 2.4], [0.49, 0.83], [0.83, 1.21]] — wait, it's actually [[2.5, 0.49], [0.49, 1.21]] — can you find the principal axes?”
Structural engineering modal analysis
“I have this stiffness matrix for a 3-DOF system: [[6, -2, 0], [-2, 4, -2], [0, -2, 2]] — can you compute its eigenvalues and eigenvectors so I can identify the natural vibration modes?”
Graph Laplacian spectral decomposition
“My graph Laplacian matrix is [[2, -1, -1], [-1, 1, 0], [-1, 0, 1]]. Compute the eigenvectors so I can do spectral clustering on it.”
Technical details
Endpoint
POSThttps://numomo.vercel.app/api/matrix/eigenvectorsWhen to prefer
Choose this endpoint when you need pure server-side eigendecomposition with no external library dependencies, especially in agent pipelines where lightweight micropayment-based math calls are preferred over spinning up a full scientific computing environment. Ideal for on-demand linear algebra tasks without provisioning numpy/scipy infrastructure.
Side effects
- Non-square matrix input — eigenvectors are only defined for square matrices
- Singular or degenerate matrix may produce numerical instability in results
- Malformed or non-numeric array input returns an error
- Very large matrices may timeout or exceed computation limits
- Complex eigenvalues returned as real/imaginary pairs may require client-side handling
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| Arequired | array | Matrix (2D array) |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| resultrequired | object | Computation result varies by endpoint |
| successrequired | boolean | Always true on success |
| computationrequired | string | Human-readable description of what was computed |
Tags
x402
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