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Sqemo
An ERD tool that enforces database naming conventions
Define a word list and naming rules once. Model in business terms and Sqemo generates consistent column names, flags overrides, and lints drift in the app, in CI, or through MCP so AI agents follow your standard. Runs in the browser, no signup.
Hi, maker here.
Every database I've worked on ended up with usr_id, userId, and user_identifier in it. Each one was written by someone following the naming convention on the wiki.
Sqemo makes the convention executable. You register a word list (customer → cust, number → no) and naming rules (case, delimiter, unknown words). Then you model in business terms, "Customer Number", and the column comes out cust_no. Same input, same name, for everyone. Overrides are allowed but flagged.
For teams: developers create ERDs → standards are checked and missing terms are suggested → an admin approves them → approved terms become part of the team's shared standards.
Drift becomes detectable: there's a linter in the app, a CLI that fails CI when a column no longer matches the word list (npx sqemo-mcp lint schema.erd.json), and an MCP server so agents editing your schema follow your naming standard too.
It runs in the browser with no signup. Everything lives in a plain .erd.json you can commit. SQL DDL round-trips in seven dialects, and DBML imports and exports if you're coming from dbdiagram.
Backstory: I'm from Korea, where government IT audits require glossary-based naming standards, so I've watched teams maintain these by hand in Excel for years.
Core is free. Pro ($9/mo) adds ALTER generation against a baseline, live DB introspection, and drift checks against a real database.
I'd be glad for feedback, especially from anyone who has tried to keep a naming convention alive on a team of more than three.
(The terminal and agent panels in the gallery are illustrative; the lint output is real.)
About Sqemo on Product Hunt
“An ERD tool that enforces database naming conventions”
Sqemo was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #159 on the daily leaderboard. Define a word list and naming rules once. Model in business terms and Sqemo generates consistent column names, flags overrides, and lints drift in the app, in CI, or through MCP so AI agents follow your standard. Runs in the browser, no signup.
On the analytics side, Sqemo competes within Productivity, Developer Tools, GitHub and Database — topics that collectively have 1.2M followers on Product Hunt. The dashboard above tracks how Sqemo performed against the three products that launched closest to it on the same day.
Who hunted Sqemo?
Sqemo was hunted by Donghyun Park. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Sqemo including community comment highlights and product details, visit the product overview.
Donghyun Park