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Mql

Mql is an open-source application that uses a connected database or uploaded schema to turn natural-language questions into SQL queries. Its documented local setup uses Docker, an OpenAI API key and PostgreSQL.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Mql — OpenViST project profile in AI Data & Analytics.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Mql when you want to translate questions about a PostgreSQL database into SQL and can provide the schema context. Its documented output is SQL generation rather than query execution or visualization.

Who it is for

  • Analytics users who want SQL generated from questions about PostgreSQL data.
  • Developers exploring a locally run, schema-aware natural-language-to-SQL application.

Documented uses

  • Provide a database connection or upload a schema.
  • Ask a question in natural language and receive a SQL query.
  • Set up a local Mql dashboard using Docker.
Before you choose

Requirements & limits

The repository is public and MIT-licensed. The README documents a local Docker setup and requires an OpenAI API key.

  • The README identifies PostgreSQL as the supported database.
  • The Docker setup requires Docker, an OpenAI API key and a configured database URL.
  • The reported accuracy figures come from the project's own 50-query test and are not an independent evaluation.
  • Query execution, MySQL support and visualizations are described as planned work.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up Mql locally with Docker

Install the local Mql dashboard using the repository's documented Docker setup.

Before you start

  • Docker installed
  • An OpenAI API key
  • A PostgreSQL database and connection details

Steps

  1. Clone the Mql repository.

  2. Add your OpenAI API key in server/Dockerfile.

  3. Set DATABASE_URL in server/.env, using postgres as the host when running the database in Docker.

  4. From the repository folder, run make install.

Expected outcome

The README says the dashboard is available at http://localhost:3000 after installation.

Guide limitations

  • The documented supported database is PostgreSQL.
  • The Docker setup creates a default login; the README advises removing it and creating a new user before production use.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
12 October 2026
Original website title
shurutech/mql · Official homepage title · retained in its source language
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