7 MCP Mistakes and How to Avoid Them | DreamFactory
When AI projects derail, it’s rarely because the model was weak. More often, failure comes from using MCP in the wrong way—forcing it to act as a universal API, data pipeline, or real-time engine instead of what it truly is: an orchestration and intelligence layer. Recently, Nate B.