Ensure that you have access to your Db2 database. This involves having valid credentials and the necessary permissions to read the data. You might need to set up a local Db2 client if you're working from a remote machine. Ensure that your local environment has the Db2 Command Line Processor (CLP) installed and configured.

Use the Db2 Command Line Processor (CLP) to run SQL queries to fetch the data you need. You can run queries like `SELECT FROM your_table;` to extract data. Redirect the output of these queries to a CSV or another intermediary file format using the `EXPORT` command. Example: `EXPORT TO data.csv OF DEL MODIFIED BY NOCHARDEL SELECT FROM your_table;`.

Ensure you have Python installed on your system. You will need the `pandas` library to read the CSV file and the `json` library to convert data into JSON format. You can install pandas using pip: `pip install pandas`.

Use the pandas library to read the CSV file into a DataFrame. This can be done with the following code snippet:
```python
import pandas as pd

df = pd.read_csv('data.csv')
```

Convert the pandas DataFrame to a JSON format using the `to_json` method. You can specify the `orient` parameter to determine how the JSON is structured. For example, using `orient='records'` will create a list of dictionaries:
```python
json_data = df.to_json(orient='records')
```

Write the JSON data to a file using Python's built-in file handling capabilities. Here is an example of how to do this:
```python
with open('data.json', 'w') as json_file:
json_file.write(json_data)
```

Open the JSON file and ensure that the data is correctly formatted and complete. You can use a JSON validator online or load the file back into Python to verify its structure:
```python
with open('data.json', 'r') as json_file:
data = json_file.read()
print(data)
```

By following these steps, you can manually move data from an IBM Db2 database to a JSON file without relying on third-party connectors or integrations.