> ## Documentation Index
> Fetch the complete documentation index at: https://docs.querybear.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Connect a database to QueryBear and query it from Claude, Cursor, or any MCP-capable AI client in under 5 minutes.

This quickstart gets you from zero to *"ask the AI a question about your data"* in about 5 minutes.

## Prerequisites

* A [QueryBear account](https://querybear.com/signup) (free tier works).
* A database to connect (PostgreSQL, MySQL, or SQLite).
* One of the supported [AI clients](/clients/claude-code).

## 1. Add a connection in the dashboard

Go to [querybear.com/dashboard](https://querybear.com/dashboard) → **Connections** → **New connection**.

Choose your database type and either paste a connection string or fill in the fields:

* **Host** — your database host (e.g. `db.example.com` or `127.0.0.1`)
* **Port** — `5432` (Postgres), `3306` (MySQL)
* **Database name**
* **User / password** — use a read-only role (see [security](/features/security))
* **SSL mode** — `require` recommended for any remote DB

For SQLite, you instead point QueryBear at the file path.

<Tip>
  For production databases, create a dedicated read-only user. QueryBear's gateway is read-only by design, but a least-privilege DB role is belt-and-suspenders. See the [Postgres](/databases/postgres), [MySQL](/databases/mysql), or [SQLite](/databases/sqlite) page for the exact `CREATE ROLE` SQL.
</Tip>

## 2. Configure access rules

After connecting, QueryBear pulls your schema. You can then:

* **Allow-list tables** — only checked tables are visible to the agent. Default is "all tables."
* **Block columns** — mark sensitive columns (password hashes, API keys, PII). They're stripped from schema responses and any query mentioning them is rejected.
* **Set a row limit** — every query gets `LIMIT n` enforced. Default `1000`.
* **Set a query timeout** — long-running queries are killed. Default `30s`.

## 3. Wire up your AI client

In the dashboard, open the **MCP Config** tab on your connection. Pick your client — Claude Code, Claude Desktop, Cursor, Codex, Windsurf, or ChatGPT — and copy the one-line config.

For example, Claude Code:

```bash theme={null}
claude mcp add --transport http querybear https://mcp.querybear.com/mcp
```

Full per-client instructions: [Claude Code](/clients/claude-code) · [Claude Desktop](/clients/claude-desktop) · [Cursor](/clients/cursor) · [Codex](/clients/codex) · [Windsurf](/clients/windsurf) · [ChatGPT](/clients/chatgpt).

## 4. Authorize the client

The first tool call from your client triggers an OAuth flow — QueryBear opens a browser tab and asks you to grant the client access to your connections. Approve, and you're done.

## 5. Ask a question

In your AI client, try:

> *"What QueryBear tools are available?"*

You should see `list_connections`, `get_schema`, and `run_query`.

Then try something real:

> *"How many users signed up in the last 7 days?"*

The agent will:

1. Call `get_schema` to learn your tables.
2. Write a SQL query.
3. Call `run_query`, which runs the query through QueryBear's security pipeline.
4. Return the result.

You can see every query the agent ran in the dashboard under **Audit log**.

## What's next?

<CardGroup>
  <Card title="Setup guides by combination" href="/guides/postgres-claude-code">
    Step-by-step guides for every database × AI client combination.
  </Card>

  <Card title="Security model" href="/features/security">
    Understand exactly what the gateway protects against.
  </Card>
</CardGroup>