I Built an MCP Server That Gives AI Trading Agents a Brain — Here's How

Published on Dev.to by AlgoVault Labs There are 20,000+ MCP servers. Most of the crypto ones do plumbing — read prices, place orders, fetch order books. None of them tell your AI agent what to do with that data. I built crypto-quant-signal-mcp — a signal interpretation layer for Hyperliquid perpetual futures. It takes raw market data and returns a single verdict: BUY, SELL, or HOLD, with a confidence score and reasoning. This post covers the architecture, the scoring logic, and the decisions I made along the way. The Problem I run quant strategies on Hyperliquid and Binance Futures. When I started using Claude and Cursor to help evaluate positions, the only MCP servers available were raw data readers or order execution tools. I'd ask Claude: "Should I go long on ETH right now?" and it would say something generic about market conditions because it had no tools to actually analyze live data. What I wanted was a tool that does what I do manually every day — check RSI, look at the EMA cros