Most builders assume that multi-year Binance historical data — the kind you need to backtest a strategy or train a model — sits behind an expensive data vendor. It doesn't. Binance publishes its entire futures price and funding history as free, checksummed ZIP files on a public CDN, with no API key and no rate limits. This is the exact dataset we use to train our HMM market-regime model: USD⃋-M perpetual futures, 1-hour klines plus funding rates, going back to January 2020. Roughly 56,000 hourly candles per long-lived symbol. For how to get the data for yourself see our blog post here: https://cryptodataapi.com/blog/free-binance-historical-data-backtesting Rule of thumb: pull raw price and funding history from the free Binance archive, and use the API for the things you can't reconstruct from candles — our regime labels, health scores, and the point-in-time snapshot archive that captures what every signal read on a given day.

Just shipped: a Model Context Protocol (MCP) server for CryptoDataAPI. This means you can plug Claude (or any MCP-compatible AI client) directly into real-time Hyperliquid perps data — funding rates, order book depth, OI, liquidations, top trader positioning — and have it reason over live market data, not stale training knowledge. Setup takes 30 seconds, COPY 1 LINE BELOW TO YOUR AI AGENT: claude mcp add cryptodataapi -- npx -y cryptodataapi-mcp Add that to your Claude MCP config and you're live. What you can do with it: - Ask Claude to analyse current funding rate extremes across all Hyperliquid markets - Have it identify OI divergences from price action in real time - Use it as a research layer while you're building — query live data in plain English - Feed it into an AI agent pipeline for autonomous signal monitoring Start asking it real questions about real-time markets! Would love to see what people build with this. Drop your use case below if you give it a go 👇