Familiarize yourself with the Postmark API documentation. You will need to understand how to authenticate and request data, such as email logs or message details, using their API endpoints. Typically, you will use HTTP requests to interact with the API.

Create a local or cloud-based environment where you can run your data transfer scripts. This could be a local development machine or a server configured with the necessary tools (e.g., Python, Node.js) required to make HTTP requests and interact with MongoDB.

Write a script to authenticate with the Postmark API using your server token. Use this script to fetch the data you need, such as email logs or message details. You can use libraries like `requests` in Python or `axios` in Node.js to make HTTP GET requests to the relevant Postmark API endpoints.

Once you receive the data from Postmark, parse the JSON response to extract relevant fields. Ensure that the data structure aligns with how you plan to store it in MongoDB. This might involve transforming the data into a format that reflects your MongoDB schema.

Establish a connection to your MongoDB database. Use a library like `pymongo` in Python or the MongoDB Node.js driver to connect to your MongoDB instance. Make sure you have the necessary credentials and access to the database.

Use your script to insert the parsed and structured data into your MongoDB collection. Ensure that you handle any potential duplicates or errors during the insertion process. This might involve checking if a record already exists in the database before inserting new data.

After inserting the data, verify that the data in MongoDB matches what was fetched from Postmark. This ensures data integrity and accuracy. Finally, consider setting up a cron job or a scheduled task to automate this data transfer process at regular intervals, depending on your needs.

By following these steps, you can successfully move data from Postmark to MongoDB without relying on third-party connectors or integrations.