Start by setting up AWS CloudTrail to record API activity and deliver the log files to an Amazon S3 bucket. Go to the AWS CloudTrail console and create a new trail. Ensure that you specify an S3 bucket where the logs will be delivered. This bucket will serve as the source from which you will extract the logs.

Create an IAM role with the necessary permissions to access the S3 bucket and read CloudTrail logs. Attach policies such as `AmazonS3ReadOnlyAccess` to the IAM role. Additionally, ensure the IAM role has permissions to write to your MongoDB destination if you are using AWS resources like EC2 to perform the data transfer.

Launch an EC2 instance in AWS that will serve as the intermediary to transfer data from S3 to MongoDB. Select an appropriate instance type based on your expected workload. Ensure that the instance has access to the IAM role configured earlier.

SSH into your EC2 instance and install necessary software such as Python and MongoDB client libraries. Use the package manager (like `apt` for Ubuntu) to install Python and then use `pip` to install the `boto3` library for accessing S3 and `pymongo` for connecting to MongoDB.

```bash
sudo apt update
sudo apt install python3-pip
pip3 install boto3 pymongo
```

Write a Python script that uses `boto3` to connect to your S3 bucket and download the CloudTrail logs. Parse these logs to transform them into a format suitable for MongoDB (e.g., JSON documents). Here’s a basic outline of the script:

```python
import boto3
import json
from pymongo import MongoClient

# Connect to S3
s3_client = boto3.client('s3')
bucket_name = 'your-cloudtrail-bucket'

# Connect to MongoDB
mongo_client = MongoClient('mongodb://your-mongodb-uri')
db = mongo_client['your_database']
collection = db['cloudtrail_logs']

# List and download logs
response = s3_client.list_objects_v2(Bucket=bucket_name)
for obj in response.get('Contents', []):
file_content = s3_client.get_object(Bucket=bucket_name, Key=obj['Key'])['Body'].read().decode('utf-8')
logs = json.loads(file_content)
transformed_logs = transform_logs(logs) # Implement this function
collection.insert_many(transformed_logs)
```

Execute the Python script on the EC2 instance to transfer the logs from S3 to your MongoDB database. This step involves processing each log file, transforming it, and then inserting it into the MongoDB collection.

```bash
python3 transfer_script.py
```

To ensure continuous data flow, automate the script execution using cron jobs on your EC2 instance. Edit the crontab file with `crontab -e` and schedule the script to run at regular intervals.

```bash
*/30 * * * * /usr/bin/python3 /path/to/transfer_script.py
```

This setup ensures that your MongoDB database is regularly updated with the latest CloudTrail logs from S3.

By following these steps, you can efficiently transfer data from AWS CloudTrail to a MongoDB destination without relying on third-party connectors or integrations.