Begin by setting up your AWS environment. Ensure you have an active AWS account with permissions to create and manage Redshift clusters. Create a new Redshift cluster via the AWS Management Console, and configure the necessary security groups and networking settings to allow access from your local machine or server where you will run the data transfer scripts.

Install the necessary tools and libraries on your local machine or server. Ensure you have Python installed, along with the `requests` library for API interaction and `psycopg2` for connecting to Redshift. Use pip to install these packages:
```
pip install requests psycopg2-binary
```

Write a Python script to access the SpaceX API. Use the `requests` library to send HTTP GET requests to the API endpoint. Choose the specific endpoint you want to collect data from, such as launches or rockets. Here is a basic example:
```python
import requests

response = requests.get('https://api.spacexdata.com/v4/launches')
data = response.json()
```

Once you've retrieved the JSON data from the SpaceX API, process and transform it into a format suitable for insertion into Redshift. This might involve flattening nested JSON structures, converting data types, and handling any missing or null values. Use Python’s built-in functions or libraries like `pandas` to clean and prepare the data.

Create a table in Redshift to store the SpaceX data. Use the Redshift Query Editor in the AWS Management Console or a SQL client to define the table schema matching the structure of your processed data:
```sql
CREATE TABLE spacex_launches (
id VARCHAR(256),
name VARCHAR(256),
date_utc TIMESTAMP,
rocket VARCHAR(256),
success BOOLEAN
-- Add more columns as necessary
);
```

Write a Python script to insert the processed data into the Redshift table. Use the `psycopg2` library to connect to your Redshift cluster and execute SQL INSERT statements. Here is an example:
```python
import psycopg2

conn = psycopg2.connect(
dbname='your_dbname',
user='your_user',
password='your_password',
host='your_redshift_cluster_endpoint',
port='5439'
)
cursor = conn.cursor()

for launch in data:
cursor.execute(
"INSERT INTO spacex_launches (id, name, date_utc, rocket, success) VALUES (%s, %s, %s, %s, %s)",
(launch['id'], launch['name'], launch['date_utc'], launch['rocket'], launch['success'])
)

conn.commit()
cursor.close()
conn.close()
```

Finally, automate the data transfer process to keep your Redshift data updated. You can use a cron job (Linux/macOS) or Task Scheduler (Windows) to schedule your Python script to run at regular intervals. This ensures your Redshift database is consistently updated with the latest data from the SpaceX API.

This guide should help you successfully transfer data from the SpaceX API to an Amazon Redshift destination using a direct approach without third-party connectors.