Where database blog posts get flame-broiled to perfection
Alright, team, gather 'round for the all-hands on our new salvation, the PlanetScale MCP server. I've read the announcement, and my eye has developed a brand new twitch. They say it'll bring our database "directly into our AI tools," which sounds just as reassuring as bringing a toddler into a server room. Here are just a few of my favorite highlights from this brave new future.
So, let me get this straight. We're connecting a Stochastic Parrot directly to our production database. The same technology that confidently hallucinates API calls and invents library functions now gets to play with customer data. I’m particularly excited for the execute_write_query permission. The blog post kindly includes this little gem:
We advise caution when giving LLMs write access to any production database. Ah, yes, "caution." I remember "caution." It’s what we were told right before that "simple"
ALTER TABLEmigration in '22 locked the entire user table for six hours during peak traffic. Giving a glorified autocomplete bot write-access feels less like a feature and more like a creative way to file for bankruptcy.
I’m very comforted by the "Safe and intelligent query execution." Specifically, the "Destructive query protection" that blocks UPDATE or DELETE statements without a WHERE clause. That’s fantastic. It will definitely stop a cleverly worded prompt that generates DELETE FROM users WHERE is_active = true;. It has a WHERE clause, so it's totally safe, right? We're not eliminating human error; we're just outsourcing it to a machine that can make mistakes faster and at a scale we can't even comprehend. This isn't a safety net; it's a safety net with a giant, AI-shaped hole in the middle.
My favorite new workflow enhancement is the "Human confirmation for DDL." It says any schema change will "prompt the LLM to request human confirmation." Wonderful. So my job, as a senior engineer with a decade of experience watching databases catch fire, is now to be a human CAPTCHA for a language model that thinks adding six new JSONB columns to a billion-row table is a "quick optimization." My pager is about to be replaced by a Slack bot asking, "Are you sure you want to drop index_users_on_email? Pretty please?" at 2 AM.
And of course, the promise of letting everyone else in on the fun. "Use natural language to learn about your data." I can already picture it: the marketing team asking, "Just pull me a quick list of all users and everything they've ever clicked on," which the AI helpfully translates into a full table scan that grinds our read replicas to a fine powder. I have PTSD from junior developers writing N+1 queries. Now we're giving the entire company a tool to invent N+Infinity queries on the fly. What could possibly go wrong?
Ultimately, this is just another layer. Another API, another set of credentials, another point of failure in a chain that's already begging to break. We’re not solving the problem of complex database interactions; we're just trading a set of well-understood, predictable SQL problems for a new set of opaque, non-deterministic AI problems. When this breaks, who do I file a ticket with? The protocol? The model? Myself, for thinking this time would be different?
Anyway, I’ve got to go update my resume. It seems "AI Query Babysitter" is a new and exciting job title.