Begin by thoroughly reading the documentation of the News API you intend to use. Make sure you understand the endpoint URL, the parameters needed (like API keys, query terms, etc.), the response format (usually JSON), and any rate limits imposed by the API provider. This understanding is crucial for efficiently extracting the data.

Use Python's built-in libraries to fetch data from the News API. You can use the `requests` library to send HTTP GET requests to the API. Install it by running `pip install requests` if not already installed. Write a Python script to construct the URL with necessary parameters and make the GET request. Process the response to ensure successful data retrieval.

```python
import requests

API_KEY = 'your_api_key'
url = f'https://newsapi.org/v2/everything?q=keyword&apiKey={API_KEY}'

response = requests.get(url)
news_data = response.json() # Assuming JSON response
```

Once the data is fetched, parse the JSON response to extract relevant fields such as article title, description, URL, publication date, etc. Transform this data into a structured format like a list of dictionaries or a pandas DataFrame for easy manipulation.

```python
import pandas as pd

articles = news_data.get('articles', [])
structured_data = [{'title': article['title'], 'description': article['description'], 'url': article['url'], 'publishedAt': article['publishedAt']} for article in articles]
df = pd.DataFrame(structured_data)
```

Ensure you have access to the MSSQL server and know the connection details. Create a database and a table to store the news data. Define appropriate columns to match the data structure (e.g., title, description, URL, publication date). You can use SQL Server Management Studio (SSMS) or any other SQL client for this task.

```sql
CREATE DATABASE NewsDatabase;
USE NewsDatabase;
CREATE TABLE NewsArticles (
ID INT PRIMARY KEY IDENTITY,
Title NVARCHAR(MAX),
Description NVARCHAR(MAX),
URL NVARCHAR(255),
PublishedAt DATETIME
);
```

Use Python's `pyodbc` or `pymssql` library to establish a connection to your MSSQL database. If not already installed, you can install `pyodbc` using `pip install pyodbc`.

```python
import pyodbc

connection_string = 'DRIVER={ODBC Driver 17 for SQL Server};SERVER=your_server;DATABASE=NewsDatabase;UID=your_username;PWD=your_password'
conn = pyodbc.connect(connection_string)
cursor = conn.cursor()
```

Iterate over the structured data and insert each record into the MSSQL table. Use parameterized queries to prevent SQL injection and ensure data integrity.

```python
for index, row in df.iterrows():
cursor.execute("INSERT INTO NewsArticles (Title, Description, URL, PublishedAt) VALUES (?, ?, ?, ?)", row['title'], row['description'], row['url'], row['publishedAt'])
conn.commit()
```

After the data insertion, verify that the data has been correctly inserted into the MSSQL table by querying the table. Once verification is done, close the database connection to release resources.

```python
cursor.execute("SELECT COUNT(*) FROM NewsArticles")
print(f"Number of records inserted: {cursor.fetchone()[0]}")
conn.close()
```

By following these steps, you can successfully move data from a News API to an MSSQL database without using third-party connectors or integrations.