Boost Supabase Performance the Smart Way (with MCP + Cursor)
So here's the thing - I've been away from my 60-day challenge for a few weeks because of construction at my house, and when I finally got back to work on my travel directory project, everything was running slower than a tourist trying to navigate Bali traffic during rush hour.
I'm talking painfully slow. The admin dashboard was crawling, the frontend felt sluggish, and I knew something was seriously wrong with my Supabase setup.
Quick summary
I discovered my Supabase database was making unnecessary authentication checks on every single row, which was killing performance. Using Cursor AI with Supabase's MCP integration, I managed to optimize the database and reduce authentication function calls by 90%. But here's the kicker - I almost broke everything in the process.
Why I'm sharing this debugging nightmare
Living here in Bali and building this travel directory, I've learned that the biggest lessons come from the messiest problems. This performance issue taught me something crucial about database optimization that I wish I'd known earlier.
Plus, I made some rookie mistakes that could've destroyed my entire database. If you're dealing with slow Supabase performance, this might save you hours of frustration (and potential disasters).
The problem that made me want to throw my laptop
When I opened my project after three weeks away, I immediately noticed the admin dashboard was taking forever to load. We're talking 10-15 seconds just to display a list of stays. The frontend wasn't much better.
At first, I thought maybe it was my internet connection here in Bali. But then I remembered having similar issues with my other project - EUR Overview, a directory for European companies. That project had the exact same sluggish behavior.
You know what's funny? I used to think slow database performance was just something you had to live with as your project grew. Turns out, I was completely wrong.
What I discovered in Supabase insights (this blew my mind)
Here's where it gets interesting. Supabase has this amazing feature called Performance Insights that I'd never really explored. When you go to the Performance tab in your dashboard, it shows you exactly what's slowing down your database.
I found warnings about Row Level Security (RLS) policies that weren't properly optimized. Basically, every time someone tried to access the admin dashboard, Supabase was checking authentication against every single row in multiple tables.
Imagine having to verify your ID at every single store in a mall just to walk through it. That's essentially what my database was doing.
My first attempt (spoiler: I was terrified)
I'll be honest - seeing those database warnings made me nervous. This isn't like fixing a CSS bug where the worst thing that happens is your button looks weird. Mess up your database configuration, and you could lose everything.
But here's where living in Bali has taught me something about taking calculated risks. Sometimes you have to trust the process, even when it's scary.
I decided to use Cursor AI with Supabase's MCP (Model Context Protocol) integration. This lets the AI actually connect to and understand your database structure, which is pretty wild when you think about it.
How I actually fixed the performance issues
Step 1: Getting the diagnosis from Supabase
First, I went to my Supabase dashboard, clicked on Performance, then opened the Performance tab. The warnings section showed me exactly what was wrong - my RLS policies were causing massive overhead.
I copied those warnings as markdown (Supabase makes this super easy) and headed over to Cursor.
Step 2: Letting AI analyze the problem
In Cursor, I pasted the warnings and wrote something like: "I feel my application is running quite slow. In Supabase I saw these optimization questions needed for authentication. We use our profiles table and check if the user is an admin by role column. Please verify this with Supabase MCP and help me optimize the database."
The key here was being specific about how my authentication works. In my database, I have a profiles table with a role column that determines if someone is an admin.
Step 3: Watching the magic happen (and holding my breath)
What happened next was honestly pretty incredible. The AI connected to my database through MCP and started making optimizations:
Fixed authentication RLS issues: Reduced authentication function calls by 90%
Removed duplicate indexes: Cleaned up redundant database indexes
Added strategic performance indexes: Created new indexes for commonly queried data
Optimized database functions: Made admin operations 58% faster
I'm not gonna lie, watching AI make direct changes to my database was both exciting and terrifying.
The stuff that went wrong (and my important warning)
Here's where I need to be brutally honest. This approach worked for me because my project is still in development and doesn't have real users or revenue yet.
If you have a live project generating revenue, DO NOT just blindly trust AI with your database. Seriously. I cannot stress this enough.
These kinds of optimizations can break authentication, corrupt data relationships, or make your app completely inaccessible. For production projects, consult someone experienced with database optimization or at least test everything on a staging environment first.
I got lucky. But luck isn't a strategy when people are depending on your platform.
The results (and what I learned)
After the optimizations, I refreshed the Performance tab in Supabase. Zero warnings. The admin dashboard started loading significantly faster, though it's still not as snappy as I'd like (I think I'm on a smaller server plan).
But here's what really impressed me - the AI created a detailed markdown file with all the optimizations it made, prioritized by importance. It even included explanations for each change, which helped me understand what actually happened to my database.
Current status and what's next
The performance issues are mostly resolved, but I realized there are still some frontend optimizations needed. The AI analysis suggested several improvements to how I'm handling data queries and component rendering.
My assistant is re-uploading images for the location pages (we had some Supabase storage issues), and I'm planning to add more listings this week. Then we can finally start testing the platform properly and set up Google Search Console and Analytics.
Lessons I'm taking from this debugging session
Supabase Performance Insights is incredibly powerful - I wish I'd discovered it sooner
AI can be amazing for database optimization - but only if you understand the risks
Taking breaks from projects isn't always bad - coming back with fresh eyes helped me spot issues I might have ignored
Document everything - having that optimization file will be invaluable for future reference
What I'm working on next
Tomorrow I'm planning a full optimization video where we'll implement the remaining performance improvements. I want to tackle the frontend speed issues and maybe dive deeper into database indexing strategies.
I'm also thinking about sharing how I built my own CRM system for my EUR Overview project. Posted about it on X and got quite a bit of interest, so that might be a good topic for the community.
Final thoughts
You know what's wild about this whole experience? I almost didn't share it because I was embarrassed about how slow my app had become. But that's exactly why these stories matter.
Building in public means showing the messy parts, not just the victories. Performance optimization isn't glamorous, but it's crucial for creating something people actually want to use.
If you're dealing with similar Supabase performance issues, hopefully this helps. Just remember - be careful with production databases, and always have backups.
Following along with my 60-day challenge? I'm documenting everything as I build this travel directory from scratch. Subscribe to catch the next episode where we'll dive deeper into those frontend optimizations.