ClickMVP is the only code generator that ships with real enterprise domain knowledge AND AI-Ready context files. → 1,800+ data models from open-source ERPs (13,799 entities, ~51k fields), no hallucinated schemas → Every project includes CLAUDE.md, AGENTS.md, DOMAIN.md, RECIPES.md so Claude/Cursor/Copilot extend it correctly → Deterministic templates, compiles 100% of the time → Also works as an MCP server for Claude, Cursor, VS Code Generated code is useless if your AI can't extend it.
Hey Product Hunt! 👋
Solo maker here. After 39 years implementing enterprise applications across dozens of industries (Oracle, SAP, Totvs Protheus), I kept noticing the same pattern: every software house starts every project the same way, 2 to 4 weeks modeling data before writing any business logic. And nobody reuses anything, even though thousands of companies have already solved the same domains.
ClickMVP is my attempt to fix that. It's a visual data modeler backed by 1,800+ real enterprise schemas (sourced from open-source ERPs like ERPNext, industry databases, and curated startup templates). You pick a domain, customize the model visually, and generate full-stack Node.js + React code that always compiles.
But here's what I'm most proud of: every project ships AI-ready. The generated code includes CLAUDE.md, AGENTS.md, DOMAIN.md and RECIPES.md, so when you open the project in Claude Code, Cursor, or Copilot, your AI already knows the architecture, the domain model, and exactly how to extend it. No hallucinating a different pattern. No reinventing your naming conventions. It just works.
For AI-native developers, ClickMVP also ships as an MCP server, so you can use it inside Claude, Cursor, or Copilot. Just say "I need a clinic management system" and it suggests Patient (32 fields), Appointment (28 fields), Medical Record (45 fields)... then generates the code.
Two insights drove this product:
1. The value isn't in generating code, it's in knowing what the right data model looks like. That's what takes weeks in real projects.
2. Generated code is useless if your AI can't extend it correctly. That's why AI-readiness is built in, not bolted on.
Happy to dive into architecture, the data sources, the MCP integration, or why I think most AI code generators are solving the wrong half of the problem.
Ask me anything! 🙌
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