Tiger SQL: Designing PostgreSQL Schemas with Transparent AI Reasoning
Jackson Kasi

Jackson Kasi @jacksonkasi

About: Self-taught tech enthusiast with a passion for continuous learning and innovative solutions

Location:
India
Joined:
Dec 25, 2020

Tiger SQL: Designing PostgreSQL Schemas with Transparent AI Reasoning

Publish Date: Jan 2
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This is a submission for the DEV's Worldwide Show and Tell Challenge Presented by Mux


🎥 My Pitch Video


🧠 What I Built

Tiger SQL is an AI-powered PostgreSQL schema builder that lets you design, edit, and evolve database schemas using:

  • Visual diagrams
  • SQL editor
  • Natural language (chat)

All three stay fully in sync.

Unlike traditional tools, Tiger SQL makes AI reasoning transparent — you can see thinking, tool calls, and MCP execution instead of black-box outputs.


🎯 The Problem

Designing database schemas is:

  • Slow and iterative
  • Error-prone under real-world constraints
  • Hard to refactor once production data exists

Most tools are either:

  • Visual but dumb
  • Or AI-powered but opaque

I wanted a tool that thinks with you, not for you.


💡 Why Tiger SQL Is Different

What makes it special:

  • Chat-driven schema design (with visible reasoning)
  • Import existing PostgreSQL schemas
  • MCP-based assistant (pg-aiguide by Timescale)
  • Bring your own OpenAI / Gemini key
  • Visual ↔ SQL ↔ Manual edits stay in sync
  • Transparent tool calls & execution steps

This makes schema evolution safer, faster, and auditable.


🛠️ How It Works (High Level)

  1. You ask questions or request changes via chat
  2. The AI reasons using MCP tools (visible step-by-step)
  3. Schema updates reflect instantly on the canvas and SQL
  4. You can fine-tune manually at any time

No magic. No lock-in. Full control.


🚀 Demo & Links

No login required — open and start designing.


🧩 Technical Highlights

  • PostgreSQL-first design
  • MCP (Model Context Protocol) integration
  • Deterministic schema updates
  • Canvas-based relationship editing
  • Search across tables & columns
  • Enum creation, FK management, indexing
  • Built for real production schemas, not toy demos

🎥 Use of Mux (Best Use of Mux Category)

Mux is used to:

  • Host the 1-minute pitch video
  • Deliver fast, high-quality playback
  • Enable easy embedding inside DEV posts

The upload + embed flow was smooth, and captions helped improve accessibility and clarity.


🧠 The Story Behind It

Tiger SQL started as a personal frustration with existing schema tools while working on real production systems.

I wanted something that:

  • Explains why a schema change makes sense
  • Helps refactor safely
  • Respects PostgreSQL best practices

It’s open-source, actively maintained, and built in public.


✅ Confirmation

By submitting this project, I confirm that my video adheres to Mux’s terms of service: https://www.mux.com/terms

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