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Quick Start

This walkthrough takes you from a brand-new account to a working, shareable query in a few minutes. Each step links to the page where it is documented in full.

1. Create an account and a group​

Sign up at app.kvery.io. When you register, Kvery creates your first group automatically — this is your workspace. You can rename it or create more groups later from the group switcher.

See: Groups overview.

2. Add a database connection​

Open the connections area and add a database connection. Choose the driver (MySQL, PostgreSQL, or MSSQL), then enter the host, port, and credentials. You can secure the connection with an SSL certificate or tunnel it over SSH. Use Test connection to confirm Kvery can reach the database before saving.

See: Database connections.

3. Write your first query​

Open the Editor, pick your connection, and write some SQL:

SELECT id, name, created_at
FROM users
ORDER BY created_at DESC;

Run it to see the results. As you type, the editor suggests your table and column names automatically.

See: The SQL Editor.

4. Save the query and choose a layout​

Save the query with a name. Kvery shows the result as a table by default, but you can switch the layout to cards or a chart and that choice is saved with the query.

See: Query results.

5. Add a parameter (optional)​

Turn a value into an input field so others can run the query safely:

SELECT id, name, created_at
FROM users
WHERE country = :country
ORDER BY created_at DESC;

Kvery detects :country and renders a form field for it. This is the foundation of Kvery's form variables.

6. Share it​

Enable sharing on the query to generate a stable hash link. Anyone with the link can run it (you can protect it with a password and an expiry date), and the same hash also exposes the query as a REST API endpoint.

See: Sharing queries.

7. Put it on a dashboard​

Create a dashboard and add your query as a tile. Combine several queries — tables, cards, and charts — into a single view you can share with your team.

See: Dashboards overview.

That is the full loop: connect → write → save → share → visualise. The rest of the documentation covers each step in depth, plus automation (scheduling), AI assistance, and the MCP server.