Even simpler stuff: - copying pasting a broken local url in cursor, and asking it to fix all console errors. Works really well. - or when you have a complex schema, and need to find some kind of specific record, you can just ask cursor "find me a user that has X transactions, matches Y condition, etc..". I found it much faster than me at finding relevant records
Example use case: https://news.ycombinator.com/item?id=43466434
This sounds risky but very useful if it works as intended!
If you know SQL and know what you're trying to find, what can the LLM do quickly that you couldn't just constructing a query to get what you want?
Alternatively if you don't know SQL, aren't you never going to learn it if every opportunity you have you bust out an LLM and hope for the best?
A buggy feature left DB in invalid state, I described the issue to Claude + Postgres MCP to both query the DB to analyze and then generate SQL scripts to fix, and validation and rollback scripts. Easy enough to do without the tooling... but with the tooling, it took probably a quarter or less of the time.
- fetch, essentially curl any webpage or endpoint
- filesystem, read(and occasionally write) to local disk
- mcp-perplexity, so I can essentially have Claude sample from perplexity's various models and/or use it for web search. Somewhat superseded by Claude's own new web search capability, but perplexity's is generally better.