Why candles aren't enough, what microstructure your agent actually needs, and how a keyless self-describing MCP schema beats hardcoded REST parsing in an agent loop.
If you've ever pointed an LLM agent at a crypto market and asked it "is something happening on SOL right now?", you've probably watched it fetch a candle endpoint, see green bars, and confidently say "yes, bullish momentum." Then the move reverses in ninety seconds and the agent has no idea why.
I build trading-adjacent agents, and the single biggest upgrade to their decision quality wasn't a smarter model or a longer prompt. It was giving them the right data over the right transport. This post is about both halves of that: what market data an agent actually needs beyond OHLCV, and why Model Context Protocol (MCP) with a self-describing schema is a better wiring than the REST-parsing glue you'd write by hand.
Disclosure: I work on MidasFlow, and the tool I'll use for the concrete examples is our MidasFlow Flow API. It's a market-data feed, not trading advice, and it has nothing to do with the Flow blockchain. I'll keep the vendor stuff to the snippets; the reasoning applies to any feed you wire up.
Why candles alone fail an agent
