How connecting the right Model Context Protocol servers in AI coding tools dramatically improves output quality
Vibe Coding / Augmented engineering tip of the week pt 3: connecting mcps really does make a big difference. Might be obvious to a lot of folks, but the quality in output really does jump up a level when you have the right mix of mcps configured in claude code or codex, etc. for your project.
My personal mcp mvp (😅) is for the database - troubleshooting issues, iterating functionality by reading actual sample records and using them as context and not just what's available in the codebase.
They can be hard to set up effectively depending on your project (dynamo 😣), but the supabase mcp is really good and postgres mcp pro is really helpful I've found once I get it dialed in.
If you're looking for an mcp that's really easy to setup and high impact, context7 is really good for improving code output when you're using frameworks that change a lot (cough nextjs, swift ecosystem, etc).
Telling your agent to use context7 mcp for e.g. next 15 and even putting it in your agents.md / claude.md / * helps get you a good response that isn't a garbled soup of code across 3 versions of the framework that's had breaking changes.
My least favorite part of the javascript / typescript ecosystem gets a lot less painful with the help of my robot friends.
What's your favorite mcp for product development workflow?
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