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26d •
Early access to AlgoBrain - 1.5 million trading strategies
Get access to AlgoBrain on Github which enables your AI agent to create unique trading strategies via a local MCP. This means 0 tokens used to return high quality data in seconds. Get it on Github >> https://github.com/Crypto-Data-API/algobrain Watch it in action here >> https://youtu.be/2h0nRmpkIsQ Quick AI prompt to install it: "git clone https://github.com/Crypto-Data-API/algobrain and set it up as a local MCP server." Then: "verify algobrain is working as local MCP server. Then use it to create a unique crypto trading strategy"
Pinned
Jul 2 •
👋 Welcome to AI Crypto Trading Builders — Start Here
Hey, glad you're here. I'm Sam — quant trader, developer, and the builder behind CryptoDataAPI.com. I've spent years building automated trading systems, crypto data pipelines, and AI-powered execution bots. This community exists because I couldn't find one that was actually built for builders. Most crypto communities are about signals, tips, and "calls." This one is about building the systems that generate your own edge. 🏗️ What this community is about: - Building automated trading bots using AI - Using real-time crypto data — QUANT predictive models order books, funding rates, OI, liquidations - Applying AI/ML to signal generation, execution, and risk management - Sharing what works, what blows up, and what you learned from both - Meet other likeminded positive builders so we can win together! 🎁 Member perk: As a member you get an exclusive discount on CryptoDataAPI.com — real-time Hyperliquid perps data, multi-exchange feeds, and endpoints built specifically for algo traders and AI agents. Check the pinned resources post for your discount code. ✅ Three things to do right now: 1. Introduce yourself → drop a reply below: what you're building, what stack you use, and what data problems you're trying to solve 2. Check the Classroom → start with Module 1 if you're new to algo trading, or jump straight to the API integration guide if you're ready to build 3. Post your first question or share a recent win! 😄 The best communities are built by the members. Say hi, share what you're working on, and let's build something real. — Sam
Jul 11 •
I made our crypto AI prompt library free
Quick one for anyone building trading bots or AI agents in here 👇 The problem with 99% of "crypto trading prompts": the model has no live data. It sounds smart and makes the whole thing up — stale funding, unknown open interest, no clue what regime we're in. So we made our prompt library free and open. The difference: **every prompt is wired to a live data endpoint**. You fetch real numbers, paste them in, and the model actually reasons over what the market is doing right now. 10 to start with — funding-rate extremes, market regime detection, open-interest divergence, whale positioning, an autonomous risk monitor, a signal generator, an MCP analyst, a Telegram alert agent, a volatility position sizer, and a regime-aware execution controller. Copy-paste, works with Claude / GPT / Gemini. Best part — one command connects your model to the data directly: `claude mcp add cryptodataapi` Then it fetches live crypto data itself. No copy-paste. Grab them free: https://cryptodataapi.com/prompts GitHub (PRs welcome): https://github.com/Crypto-Data-API/cryptodataapi-prompt-library If you want the full-universe quant/whale/per-coin feeds, first 10 signups here get **20% off with code `SOCIAL20`**. Free key runs most of the prompts. Not financial advice — it's data, structure, and risk framing. What prompt should I add next?
Jul 9 •
Free Binance Historical Data - Useful for Backtesting
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.
Jul 6 •
🤖 One line to connect Claude directly to live crypto market data
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 👇
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