Koko Finance Python SDK

Python SDK for the Koko Finance credit card intelligence API.

Analyze credit card portfolios, compare cards side-by-side, get spending-based recommendations, check whether a card is worth renewing, and get merchant-level advice — all with a few lines of Python.

Installation

pip install koko-finance

Quick Start

from koko_finance import KokoClient

client = KokoClient(api_key="koko_your_api_key")

# Analyze your credit card portfolio
analysis = client.analyze_portfolio(
    cards=[
        {"card_name": "Chase Sapphire Preferred", "annual_fee": 95},
        {"card_name": "American Express Gold Card", "annual_fee": 250},
        {"card_name": "Citi Double Cash", "annual_fee": 0},
    ],
    spending={"dining": 500, "travel": 300, "groceries": 600, "gas": 150},
    primary_goal="travel",
)
print(analysis)

API Reference

KokoClient(api_key, base_url, timeout)

Parameter	Type	Default	Description
api_key	str	required	Your Koko API key (format: koko_xxxxx)
base_url	str	https://kokofinance.net	API base URL
timeout	int	30	Request timeout in seconds

analyze_portfolio(cards, spending, primary_goal, credit_tier, issuer_preferences, benefit_selections, verbose)

Analyze 1-10 credit cards for total value, per-card verdicts (KEEP/OPTIMIZE/CANCEL), and break-even analysis.

# Fast (default, <100ms) — deterministic calculations
analysis = client.analyze_portfolio(
    cards=[
        {"card_name": "Chase Sapphire Preferred", "annual_fee": 95},
        {"card_name": "American Express Gold Card", "annual_fee": 250},
    ],
    spending={"dining": 500, "travel": 300, "groceries": 400},
    primary_goal="travel",
)

# With benefit selections (only selected benefits count at 100%)
analysis = client.analyze_portfolio(
    cards=[
        {"card_name": "American Express Platinum Card", "annual_fee": 695},
    ],
    spending={"dining": 500, "travel": 300},
    benefit_selections=["uber", "airline_fee", "digital_entertainment", "saks"],
)

# Verbose (3-5s) — adds AI-generated narrative
analysis = client.analyze_portfolio(
    cards=[...],
    spending={"dining": 500, "travel": 300},
    verbose=True,
)

compare_cards(cards, spending, primary_goal, issuer_preferences, verbose)

Compare 2-3 credit cards side-by-side with fees, rewards, net value, and break-even.

# Fast (default, <100ms) — structured data, no AI winner
comparison = client.compare_cards(
    cards=[
        {"card_name": "Chase Sapphire Preferred", "annual_fee": 95},
        {"card_name": "Capital One Venture X", "annual_fee": 395},
    ],
    spending={"dining": 400, "travel": 500},
    primary_goal="travel",
)

# Verbose (3-5s) — adds AI-generated winner and pros/cons
comparison = client.compare_cards(cards=[...], verbose=True)

recommend_card(category, spending, primary_goal, credit_tier, portfolio_card_names, issuer_preferences, verbose)

Get the best card recommendations for a spending category.

# From the full market (always fast)
recs = client.recommend_card(
    category="dining",
    spending={"dining": 600},
    credit_tier="excellent",
)

# From your existing portfolio (fast, <100ms)
recs = client.recommend_card(
    category="dining",
    portfolio_card_names=["Chase Sapphire Preferred", "Citi Double Cash"],
)

# From portfolio with AI narrative (verbose, 2-4s)
recs = client.recommend_card(
    category="dining",
    portfolio_card_names=["Chase Sapphire Preferred", "Citi Double Cash"],
    verbose=True,
)

check_renewal(card, spending, primary_goal, issuer_preferences, benefit_selections)

Check if a card is worth keeping at annual fee renewal time.

renewal = client.check_renewal(
    card={"card_name": "Chase Sapphire Preferred", "annual_fee": 95},
    spending={"dining": 400, "travel": 300},
)
# renewal["verdict"] is "RENEW", "DOWNGRADE", or "CANCEL_AND_REPLACE"

# With benefit selections (only selected benefits count at 100%)
renewal = client.check_renewal(
    card={"card_name": "Amex Platinum"},
    spending={"dining": 400, "travel": 300, "groceries": 500},
    benefit_selections=["uber", "airline_fee", "digital_entertainment"],
)

get_benefit_categories()

Get all valid benefit keys grouped by category (no authentication required). Use the returned keys with benefit_selections in analyze_portfolio() and check_renewal().

categories = client.get_benefit_categories()
print(categories["all_keys"])  # ['admirals_club', 'airline_fee', 'dining', ...]

# Use in portfolio analysis
analysis = client.analyze_portfolio(
    cards=[...],
    benefit_selections=["uber", "dining", "admirals_club"],
)

health()

Check API health status (no authentication required).

status = client.health()

which_card_at_merchant(merchant, amount, portfolio)

Find the best card from your portfolio for a purchase at a specific merchant. Auto-detects the spending category (e.g. Starbucks -> dining) and ranks your cards by reward value.

result = client.which_card_at_merchant(
    merchant="Starbucks",
    amount=35,
    portfolio=["Chase Sapphire Reserve", "Amex Gold", "Citi Double Cash"],
)
print(result["recommended_card"])  # "American Express Gold Card"
print(result["category_detected"])  # "dining"
print(result["reason"])  # "Starbucks codes as dining — Amex Gold 4x vs ..."

merchant_benefits(merchant, portfolio)

Check if any cards in your portfolio have credits at a specific merchant. Returns matching credits with value, frequency, and schedule, plus an earning recommendation.

result = client.merchant_benefits(
    merchant="Saks Fifth Avenue",
    portfolio=["Amex Platinum", "Chase Sapphire Reserve"],
)
for b in result["matching_benefits"]:
    print(f"{b['card']}: {b['name']} - ${b['value']} ({b['frequency']})")

card_benefits(card)

Get all credits, benefits, and rewards multipliers for a specific card.

result = client.card_benefits(card="Amex Platinum")
print(f"Total credit value: ${result['total_credit_value']}")
for c in result["credits"]:
    print(f"  {c['name']}: ${c['value']}")

Error Handling

The SDK raises typed exceptions for API errors:

from koko_finance import KokoClient, RateLimitError, AuthenticationError

client = KokoClient(api_key="koko_your_api_key")

try:
    result = client.analyze_portfolio(cards=[...])
except AuthenticationError:
    print("Invalid API key")
except RateLimitError as e:
    print(f"Rate limited. Retry after {e.retry_after} seconds.")

Exception	HTTP Status	When
AuthenticationError	401	Invalid or missing API key
RateLimitError	429	Rate limit exceeded (60 req/min)
ValidationError	400, 422	Invalid request parameters
ServerError	500	API server error
KokoError	other	Base exception for all API errors

Spending Categories

The spending parameter accepts monthly dollar amounts for these categories:

Category	Key	Example
Groceries	groceries	600
Dining	dining	400
Travel	travel	200
Gas	gas	150
Streaming	streaming	45
Shopping	shopping	300
Other	other	200

Links

• Developer Docs
• Interactive API Docs (Swagger)
• GitHub

License

MIT