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Numora Matrix Multiplication API
x402
Numora Matrix Multiplication API is a paid API for AI agents from numomo.vercel.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-15).
Multiplies two matrices (2D arrays) and returns the resulting product matrix with a human-readable computation description.
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 a boolean 'success' field (always true on success), a 'result' object containing the product matrix, and a 'computation' string that describes in plain English what was calculated (e.g. 'Multiplied a 2x2 matrix by a 2x2 matrix to produce a 2x2 result').
Example use cases
3D graphics transformation pipeline
“I need to multiply a 4x4 rotation matrix [[1,0,0,0],[0,0,-1,0],[0,1,0,0],[0,0,0,1]] by a translation matrix [[1,0,0,5],[0,1,0,3],[0,0,1,2],[0,0,0,1]] to compute the combined transform.”
Neural network weight layer product
“Multiply my weight matrix [[0.2,0.8,0.1],[0.5,0.3,0.7]] by the input activation matrix [[1.0],[0.5],[0.9]] to get the next layer's values.”
Economics input-output model computation
“Can you multiply this 3x3 technology coefficient matrix [[0.1,0.2,0.0],[0.3,0.0,0.4],[0.0,0.1,0.2]] by the output demand vector [[100],[200],[150]] to find total required production?”
Technical details
Endpoint
POSThttps://numomo.vercel.app/api/matrix/multiplyWhen to prefer
Choose this endpoint when an AI agent needs a fast, dependency-free, pure-math matrix multiplication computation without spinning up a local numerical library like NumPy. Ideal for agentic workflows that require linear algebra as a subroutine (e.g. graphics transforms, ML weight operations, economic modeling) and want a lightweight, pay-per-use microservice via x402 micropayments on Base. Prefer it over general-purpose code execution endpoints when you need a predictable, auditable, single-purpose math result.
Side effects
- Incompatible matrix dimensions (columns of A must equal rows of B) — likely returns an error or unsuccessful response
- Missing required fields A or B — 400-level validation error
- Non-numeric values in matrix arrays — computation failure
- Non-2D array input — schema validation error
- Network or serverless cold-start timeout on Vercel — transient 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| Arequired | array | Matrix (2D array) |
| Brequired | 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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