Introduction
The Problem
Section titled “The Problem”Every team has databases. PostgreSQL, MongoDB, BigQuery, MySQL, ClickHouse, Redshift — often several at once. The tools to work with them haven’t changed in years:
- SQL clients (pgAdmin, DataGrip, DBeaver) give you a query editor and a schema tree. That’s it. No intelligence, no memory, no assistance.
- ChatGPT/Claude can write SQL, but can’t see your actual schema, can’t execute queries, and hallucinate column names.
- BI tools (Metabase, Looker) are for dashboards, not exploration. Building a one-off query means leaving the tool.
You end up copying schemas into ChatGPT, pasting queries into your SQL client, fixing errors, going back to ChatGPT — a manual loop that shouldn’t exist.
What Mako Does
Section titled “What Mako Does”Mako is a SQL client where the AI is the interface.
- Universal Database Client — One console that connects to PostgreSQL, MongoDB, BigQuery, MySQL, ClickHouse, Redshift, SQLite, and Cloudflare D1. Switch between databases without switching tools.
- AI Agent with Real Access — The agent inspects your actual schemas, writes queries, executes them against your real data, reads the results, and iterates. No copy-pasting. No hallucinated column names.
- Console-First Design — The agent doesn’t just answer in chat. It places working queries directly in your console editor, ready to run, save, or modify.
- Learns Your Database — A self-directive system lets the agent build persistent knowledge about your schema, naming conventions, and common patterns. It gets better the more you use it.
- Collaboration — Multi-tenant workspaces with shared consoles, saved queries, and team management.
Architecture at a Glance
Section titled “Architecture at a Glance”┌─────────────┐ ┌──────────────┐│ React App │ │ Hono API ││ (Vite) │──│ (Node.js) │└─────────────┘ └──────┬───────┘ │ ┌──────┴───────┐ │ │ ┌──────┴──────┐ ┌────┴─────┐ │ Query │ │ AI Agent │ │ Runner │ │ (Vercel │ │ (9 drivers) │ │ AI SDK) │ └─────────────┘ └──────────┘Next Steps
Section titled “Next Steps”- Getting Started — Run Mako locally in 5 minutes
- AI-Powered SQL Client — How the AI agent works
- Console — The query editor and its API
- Query Runner — Supported databases and drivers