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Numora Linear Programming Solver
x402
Numora Linear Programming Solver is a paid API for AI agents from numormo.vercel.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-14).
Solves linear programming optimization problems given an objective function and constraints using the simplex or related method
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 flag, a result object containing the optimal variable values and the optimal objective function value, and a human-readable computation string describing what was solved and the outcome. If the problem is infeasible or unbounded, this is indicated in the response.
Example use cases
Production mix optimization
“I run a factory that can make three products. The profit per unit is [5, 4, 3], the resource usage per product is A=[[6,4,2],[1,2,1.5],[0,3,5]], and I have resource limits of b=[240,60,150]. What production quantities maximize my total profit?”
Minimum cost diet planning
“Help me find the cheapest combination of foods that meets my nutritional requirements — the cost per unit of each food is c=[2,3.5,1.8], the nutrient content matrix is A=[[1,0,1],[0,2,1],[3,1,0]], and I need at least b=[4,6,3] units of each nutrient.”
Resource allocation for a project portfolio
“I have 4 projects with expected returns c=[10,15,7,12], each using budget and labor per unit given by A=[[3,2,1,4],[1,3,2,1]], with total available budget and labor b=[100,80]. Which combination of project investments maximizes my returns?”
Technical details
Endpoint
POSThttps://numormo.vercel.app/api/solve/linear-programmingWhen to prefer
Choose this endpoint when you need a pure server-side linear programming solver with no external dependencies and pay-per-use micropayment pricing. Ideal for agents that need on-demand LP solving without managing a math library, a Python runtime, or a subscription. Best for standard LP problems expressed as Ax≤b with a linear objective c·x. If you need mixed-integer programming, nonlinear optimization, or quadratic objectives, look for a more specialized solver.
Side effects
- Infeasible problem — constraints cannot be simultaneously satisfied, returns error or infeasibility flag
- Unbounded problem — objective can grow without limit, returns unbounded indicator
- Malformed matrix dimensions — A, b, c have inconsistent sizes, returns validation error
- Missing required fields A, b, or c — returns 400-level error
- Non-numeric values in input arrays — returns parsing or validation error
- Payment failure — x402 micropayment not completed, returns 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| Arequired | array | |
| brequired | array | |
| crequired | array | Objective coefficients |
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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