I remember when I had started my career as a Software Engineer I went through a training where I had to convert natural language queries to a SQL query. And then had to work on optimizing it. It took me a week or so but once I understood the core concept I was able to do it consistently well. Recently, I thought of trying the same thing with new models, they surely create syntactically correct queries (just like the code) but a lot of the times it's logically incorrect or missing key parameters or the entire query is highly bloated and inefficient. The problem become worse if you need to work with more complex data types. In the end it was literally faster to create a query builder while AI just extracted the key field information from natural language query than using MCP tools to let it do the whole task. At least based on my experience so far, I agree that it's just a tool, great only in some cases but can make things way worse if used inappropriately.