Is MCP Worth It for Algorithmic Trading? The Reality Behind Data, Latency, and Execution

If you're building in algo trading, you've probably come across MCP (Market Control/Connectivity Platforms) or similar infrastructure layers promising cleaner data access, unified feeds, and faster execution. But the real question is: 👉 Is it actually worth it? The Reality Most People Don’t Say MCP sounds great on paper — unified APIs, standardized data, lower integration overhead. But in practice, for algo trading, your edge rarely comes from how clean your API looks. It comes from: Data quality (tick accuracy, gaps, consistency) Latency (especially for lower timeframes) How you structure and interpret price behavior And this is where MCP can fall short. Most MCP-style systems: Add abstraction layers → more latency Normalize data → sometimes lose important microstructure details Lock you into their ecosystem That’s fine for dashboards or retail tools. But for serious trading systems? It can become friction. When MCP Does Make Sense To be fair, MCP is useful if: You’re building a multi