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Numora Constraint Solver API
x402
Numora Constraint Solver API is a paid API for AI agents from numomo.vercel.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-13).
Solves systems of constraints over named variables and returns feasible solutions or optimal values
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 solved variable values or feasibility determination, and a human-readable computation string describing what was computed and how the constraints were resolved.
Example use cases
Resource budget allocation
“I have three budget categories A, B, and C that must sum to $500,000. A must be at least $100,000, B between $50,000 and $200,000, and C at most $150,000. Find me values for A, B, and C that satisfy all those constraints.”
Diet or nutrition planning
“I need to find quantities of food items protein_g, carbs_g, and fat_g such that total calories equal 2000, protein is at least 150g, carbs are between 100 and 250g, and fat is no more than 80g. Can you solve for valid amounts?”
Workforce scheduling feasibility
“Given variables for day_shift_workers and night_shift_workers, check if it's feasible to satisfy: total workers equals 50, day shift is at least 30, night shift is at least 15, and day shift plus night shift cannot exceed 50.”
Technical details
Endpoint
POSThttps://numomo.vercel.app/api/solve/constraintWhen to prefer
Choose this endpoint when you need to find variable assignments that satisfy a set of mathematical constraints without relying on any external data sources or services. It is ideal for constraint satisfaction problems, feasibility checks, and bounded optimization where all logic is purely mathematical. Prefer it over general-purpose LLM reasoning for constraint problems because it returns exact, verifiable numeric solutions. It is well-suited for budget allocation, scheduling feasibility, resource planning, and any scenario where you have named variables and a list of inequality or equality constraints.
Side effects
- Infeasible system — constraints are contradictory and no solution exists
- Missing required fields — variables or constraints array not provided
- Malformed constraint expressions — unparseable syntax in constraint strings
- Underdetermined system — too few constraints to produce a unique solution
- Payment failure — x402 micropayment not completed or insufficient USDC balance
- Timeout — overly complex constraint systems may exceed compute limits
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| variablesrequired | object | |
| constraintsrequired | 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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