> For the complete documentation index, see [llms.txt](https://docs.trymito.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.trymito.io/mito-ai/database-connectors.md).

# Database Connectors

Use Mito AI to query you databases in natural language.

With Mito AI, you can get answers from your database without writing a single line of SQL.

### Initial Setup

{% embed url="<https://www.youtube.com/watch?v=sJgphOrmZb4>" %}

You can connect your database from the **Settings** page, under the **Database** tab.&#x20;

The first time you connect, it may take a few seconds while Mito AI analyzes your tables and columns.

### Using Your Database in Chat&#x20;

In the chat task pane, you can ask questions about your database. Mito AI will usually detect and use the connected database automatically, even if you don’t mention it explicitly.

That said, being specific—such as naming a table or column—often improves the accuracy of responses.

Alternatively, you can use the **@** key to bring up the variable dropdown menu, where you can search for you database (using its alias), and explicitly reference the database.&#x20;

### FAQs

#### **What databases are supported?**

Currently Mito AI supports:

* Microsoft SQL Server
* MySQL
* Oracle
* PostgreSQL
* Snowflake
* SQLite

#### **Do you store my database credentials?**&#x20;

No. Your database credentials are stored locally on your machine. Mito AI references your credentials through a local config file when establishing a connection.

Your credentials are never sent to our servers or stored remotely.


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.trymito.io/mito-ai/database-connectors.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.