MySQL connector

The MySQL connector imports data from your MySQL database into Mammoth as a dataset. Import entire tables or write custom SQL queries to select specific rows, columns, or joined data. Mammoth offers AI-assisted query generation when it is enabled for your workspace, and you can refresh the dataset manually or on a schedule.

Before you start

You need:

• A MySQL server accessible from the internet
• A database user with SELECT permission on the tables you want to import
• Your server's hostname or IP address, port (default: 3306), database name, username, and password
• Mammoth's IP address added to your MySQL firewall allowlist—see Network requirements

Step 1: Select the MySQL connector

1. In Mammoth, go to Data Library and click + New Dataset
2. Select Connectors
3. Search for MySQL
4. Click the MySQL tile

Step 2: Create a connection

Click New Connection to open the credential form.

Field	Description	Example
Host URL	Hostname or IP address of your MySQL server	mysql.example.com
Port	TCP port MySQL listens on	3306 (default)
Username	Database user with SELECT access	mammoth_reader
Password	Password for the database user	—
Database	Name of the database to connect to	ecommerce_db
Display Name	Optional label for this connection in Mammoth	MySQL Production

Tip: Mammoth needs network access
Your MySQL server must allow inbound connections from Mammoth's IP address, which the connection form shows. See Network requirements for configuration steps, including the user setup needed for external access.

After filling in the fields, click Connect. Mammoth validates the credentials and saves the connection; if validation fails, the error message appears at the bottom of the form.

Step 3: Select a table and query your data

After you connect, select the connection under Existing Connections to open the query builder. The List of tables panel shows all tables in your database. Click a table name to load a SELECT * query for it and its preview.

To write a custom query, edit the SQL in the Enter SQL query editor. MySQL uses backtick quoting for identifiers:

SELECT `order_id`, `customer_id`, `total_amount`, `created_at`
FROM `orders`
WHERE `created_at` >= DATE_SUB(NOW(), INTERVAL 90 DAY)
  AND `status` = 'shipped'

Click Run to preview results.

AI query generation

When enabled for your workspace, the Describe the data you need... box appears above the query editor. Use it to tell Mammoth what you want in plain language—for example, "all shipped orders in the last 90 days with customer IDs"—and click the generate button. Mammoth writes the SQL query based on your table structure and description. The box is disabled while Mammoth sets up metadata for AI query.

See Understanding data preview & query for a full guide.

Step 4: Save the MySQL dataset

1. Enter a dataset name in the Save table as field
2. Check the Update Method (the default is Replace all data). To change it, click the edit icon, pick an option, and click Save changes:
   • Replace all data—Replaces all existing data
   • Add new data—Adds new data based on a unique sequential column
   • Replace with new data—Replaces existing data with new data based on a unique sequential column For Add new data and Replace with new data, also choose a Key column—a numeric or date column with incrementing values, such as an ID or a date.
3. Click Save as dataset. When the dataset is saved, click Done

Keep MySQL data up to date

Set up a Dataset Refresh automation to refresh your MySQL dataset on a schedule.

Troubleshoot MySQL connections

Connection fails

• Confirm Mammoth's IPs are allowed in your MySQL grants and firewall

• Check that your MySQL user has an external host entry, not just localhost:

  CREATE USER 'mammoth_reader'@'%' IDENTIFIED BY 'password';
  GRANT SELECT ON your_database.* TO 'mammoth_reader'@'%';