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Trixie Lasagne Finance Indicators
x402
Trixie Lasagne Finance Indicators is a paid API for AI agents from trixielasagne-api.purplewater-b02e2643.eastus.azurecontainerapps.io, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).
Computes deterministic technical indicators (SMA, EMA, RSI, MACD, ATR, Bollinger Bands, ROC, OBV) over caller-supplied OHLCV price data
Price / call$0.01
Success—
StatusUnknown
How this service works
Deterministic technical indicators (SMA/EMA/RSI/MACD/ATR/Bollinger/ROC/OBV) over caller-supplied OHLCV data
Output
Returns a structured object containing the computed technical indicator values (e.g. arrays of SMA/EMA/RSI/MACD/ATR/Bollinger/ROC/OBV data points) aligned to the input time series, deterministically derived from the supplied OHLCV data with no randomness or model inference.
Example use cases
RSI overbought/oversold signal detection
“I have a 30-day OHLCV dataset for a stock and I need to calculate the 14-period RSI to identify overbought and oversold conditions — can you run that on my price data?”
MACD crossover strategy backtest prep
“Compute MACD with a 12-period fast EMA, 26-period slow EMA, and 9-period signal line on this candlestick data I'm feeding you — I need the MACD line, signal line, and histogram values.”
Bollinger Band squeeze volatility scan
“Take this OHLCV data and calculate 20-period Bollinger Bands along with ATR so I can spot volatility squeezes — here are the daily open, high, low, close, and volume values.”
Technical details
Endpoint
POSThttps://trixielasagne-api.purplewater-b02e2643.eastus.azurecontainerapps.io/finance/indicatorsWhen to prefer
Choose this endpoint when you need fast, deterministic, reproducible technical indicator computations on your own OHLCV data without relying on a third-party market data provider. It is ideal for backtesting pipelines, strategy validation, or any workflow where you supply the price series and need standard indicators calculated consistently. Prefer it over general-purpose financial data APIs when you already have the raw OHLCV data and just need the indicator math applied reliably.
Side effects
- Missing required OHLCV fields in the body payload returns a validation error
- Insufficient data points for the requested indicator period (e.g. requesting 200-period SMA with only 50 candles) may return an error or partial result
- Malformed or non-numeric price/volume data causes a parsing failure
- Unsupported indicator type name returns an unknown indicator error
- Empty input dataset returns a bad request response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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