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WealthPulse Credit Card Rewards Finder
x402
WealthPulse Credit Card Rewards Finder is a paid API for AI agents from wealthpulse.theaslangroupllc.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-14).
Ranks credit cards by net annual value after fees based on a user's personal spending profile across travel, dining, groceries, gas, and cashback categories
Price / call$0.1
Success—
StatusUnknown
How this service works
Which credit card is actually worth it for my spending? Rewards card finder that ranks cards by net annual value after fees — factoring rewards rate and signup bonuses for your spend profile (travel, dining, groceries, gas, cashback). For personal-finance and wealth agents.
Output
A ranked list of credit cards ordered by net annual value for the given spending profile, including each card's rewards rate per category, annual fee, estimated annual rewards earned, signup bonus value, and final net annual value calculation.
Example use cases
Find my best rewards card for rotating categories
“I spend heavily on different things each month — sometimes it's groceries, sometimes dining out, sometimes gas. Which credit card would actually maximize my rewards across all these categories after I account for the annual fee?”
Determine if premium card's fee is worth it
“I'm thinking about upgrading to that fancy $550 annual fee card everyone talks about, but I want to know if my actual spending habits would earn enough rewards to justify paying that much every year. Can you run the numbers for me?”
Optimize wallet for my current lifestyle
“My spending has changed a lot this year — I'm traveling way more for work and eating out constantly. Should I switch to a different rewards card, or is my current one still the best option based on how I'm actually spending money now?”
Technical details
Endpoint
GEThttps://wealthpulse.theaslangroupllc.com/api/wealth/cardsWhen to prefer
Use this endpoint when a user wants a personalized, math-driven credit card recommendation based on their actual spending breakdown rather than generic editorial rankings. Ideal for personal finance agents helping users optimize their wallet or decide whether a premium card's annual fee is justified by their specific habits.
Side effects
- Missing or zero spend inputs may return generic rankings not personalized to the user
- Spending categories outside supported buckets may be ignored or misclassified
- Signup bonus eligibility assumptions may not account for existing cardholder status
- API may return 402 if USDC payment not properly attached
- Stale card data if issuer terms have changed since last update
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"top_cards": [
{
"rank": 1,
"issuer": "Chase",
"verdict": "Best all-around travel card for this spend level",
"best_for": "travel and dining spend",
"card_name": "Chase Sapphire Preferred",
"annual_fee": "$95",
"key_rewards": [
"3x dining",
"2x travel"
],
"signup_bonus": "60,000 points ($750 travel) after $4,000 spend in 3 months",
"credit_score_needed": "good",
"estimated_annual_value": "$680"
}
],
"disclaimer": "Card offers and bonuses change frequently. Verify current terms before applying. This is not financial advice.",
"amazon_link": "https://www.amazon.com/s?k=credit+card+rewards+optimization&tag=pulsenetwork7-20",
"amazon_search": "credit card rewards optimization",
"monthly_spend": "$3,000",
"spend_profile": "travel",
"strategy_note": "Pair with a flat 2% cashback card for categories outside travel and dining",
"current_rate_context": "Average credit card APR is 21%+ (FRED data) — paying in full each month matters more than the rewards rate"
}
}Tags
x402
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