To start, you'll need to enable the Google Search Console API and create credentials in the Google Cloud Console. Navigate to the Google Cloud Console, create a new project, and enable the Search Console API. Create OAuth 2.0 credentials and save the client ID and client secret, which will be used for authentication.

You'll need to use Python to interact with the Google Search Console API. Install the necessary libraries using pip:
```bash
pip install google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client mysql-connector-python
```
These libraries will help you authenticate with Google and interact with your MySQL database.

Use the credentials obtained in Step 1 to authenticate and gain access to the API. Create a Python script that uses the OAuth 2.0 flow to obtain an access token:
```python
from google.oauth2 import service_account
from googleapiclient.discovery import build
SCOPES = ['https://www.googleapis.com/auth/webmasters.readonly']
SERVICE_ACCOUNT_FILE = 'path/to/your-service-account-file.json'
credentials = service_account.Credentials.from_service_account_file(
SERVICE_ACCOUNT_FILE, scopes=SCOPES)
service = build('webmasters', 'v3', credentials=credentials)
```
Replace `'path/to/your-service-account-file.json'` with the path to your service account JSON file.

Write a function to query data from Google Search Console using the authenticated service. For example, to get search analytics data:
```python
def get_search_analytics(site_url, start_date, end_date):
request = {
'startDate': start_date,
'endDate': end_date,
'dimensions': ['query'],
'rowLimit': 1000
}
response = service.searchanalytics().query(siteUrl=site_url, body=request).execute()
return response.get('rows', [])
```
Customize `site_url`, `start_date`, and `end_date` to fit your needs.

Ensure you have a MySQL database ready to store the data. Create a table structure that matches the data you will be importing. Here is an example SQL command to create a table:
```sql
CREATE TABLE search_analytics (
query VARCHAR(255),
clicks INT,
impressions INT,
ctr FLOAT,
position FLOAT
);
```

Use MySQL Connector in Python to insert the data into your MySQL database. Here is a sample code snippet to perform the insertion:
```python
import mysql.connector
def insert_data_to_mysql(data):
connection = mysql.connector.connect(
host='your_mysql_host',
user='your_mysql_user',
password='your_mysql_password',
database='your_mysql_database'
)
cursor = connection.cursor()
insert_query = """
INSERT INTO search_analytics (query, clicks, impressions, ctr, position)
VALUES (%s, %s, %s, %s, %s)
"""
for row in data:
cursor.execute(insert_query, (row['keys'][0], row['clicks'], row['impressions'], row['ctr'], row['position']))
connection.commit()
cursor.close()
connection.close()
search_data = get_search_analytics('https://yourwebsite.com', '2023-01-01', '2023-01-31')
insert_data_to_mysql(search_data)
```

To keep your MySQL database updated, automate the script execution using a task scheduler like cron (Linux) or Task Scheduler (Windows). Set the script to run at your desired frequency, such as daily or weekly, to ensure fresh data is consistently imported.
By following these steps, you can efficiently transfer data from Google Search Console to a MySQL database without relying on third-party connectors or integrations.