{"uid":"cap_4k1sqQbsA8dhxEkKOPv3t","slug":"api-carbon-cashmere-de-088e90f3","name":"Carbon Cashmere Crypto ML Feature Vector API","description":"Get 34 quantitative ML features across 10 categories — price returns, volatility (7d/30d), volume ratio, RSI/MACD momentum, Fear & Greed sentiment, HMM regime probabilities, orderbook imbalance, options put/call ratio, implied volatility. Per-coin feature vector for BTC, ETH, SOL, and more. AI agent API for feature engineering, custom ML model input, and quantitative crypto research.","url":"https://api.carbon-cashmere.de/v1/features/:var1","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method"],"properties":{"type":{"type":"string","const":"http"},"method":{"enum":["GET","HEAD","DELETE"],"type":"string"},"pathParams":{"type":"object","required":["coin"],"properties":{"coin":{"enum":["AAVE","ADA","APT","ARB","ATOM","AVAX","BCH","BNB","BTC","DOGE","DOT","ETC","ETH","HBAR","HYPE","ICP","KAS","LINK","LTC","MATIC","NEAR","ONDO","OP","SKY","SOL","SUI","TAO","TON","TRX","UNI","XLM","XMR","XRP","ZEC"],"type":"string","examples":["AAVE","ADA","APT","ARB","ATOM","AVAX","BCH","BNB","BTC","DOGE"],"description":"Cryptocurrency ticker symbol (uppercase). 34 supported coins."}},"additionalProperties":false},"queryParams":{"type":"object","properties":{}}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object","properties":{"coin":{"type":"string"},"features":{"type":"object"},"feature_count":{"type":"integer"}}}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_xWkw6ADZA5z7fdpRiBA4M","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Returns 34 quantitative ML features across 10 categories (price returns, volatility, volume, momentum, sentiment, HMM regimes, orderbook, options, IV) for a single cryptocurrency","exampleAgentPrompt":"Pull the full 34-feature ML vector for BTC from Carbon Cashmere — I need the price returns, volatility, RSI, MACD, Fear & Greed, HMM regime probabilities, orderbook imbalance, put/call ratio, and implied volatility to feed into my model.","exampleUseCases":null,"resultDescription":"A JSON object containing the coin ticker, a feature_count integer (34), and a features object with 34 named quantitative values spanning 10 categories: price returns, 7d/30d volatility, volume ratio, RSI momentum, MACD momentum, Fear & Greed sentiment, HMM regime probabilities, orderbook bid/ask imbalance, options put/call ratio, and implied volatility.","failureModes":["Unsupported coin ticker returns 400 or 422 — only 34 specific tickers are supported (BTC, ETH, SOL, etc.)","Payment failure (x402) if USDC not provided — endpoint costs $0.01 USDC per call","Upstream data unavailability for options or orderbook features may return partial or null values","Rate limiting if too many requests are made in short succession","Network timeout if upstream data sources are slow to respond"],"whenToPreferThis":"Choose this endpoint when you need a pre-computed, ready-to-use ML feature vector for a single cryptocurrency combining multiple signal categories (technical, sentiment, microstructure, derivatives) into one call. Ideal for feature engineering pipelines, custom ML model inference, and quantitative crypto research where you want a curated set of 34 standardized features rather than assembling them from multiple data sources yourself.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T18:41:20.742Z","isFirstParty":false}