The Scenario
A developer on your team has 30 internal staging API endpoints listed in a Google Sheet — column A has the URL, column B has the JSON request body. The task is to hit each endpoint via POST, routed through Scrape.do's proxy, to verify geo-blocking behavior and confirm that responses from different originating countries differ as expected.
The engineer who set up the staging environment is on vacation. The test results need to be in the QA report by Thursday for the compliance review.
The bad version:
- Open a REST client (Postman, curl, whatever is available), copy the URL from row 2 of the sheet, paste the JSON from column B, configure the proxy header manually with your Scrape.do token, fire the request
- Read the response status and body, type both values into columns C and D of the sheet
- Repeat 29 more times, stopping when row 14 fails with an unexpected 422 and you have to figure out whether the payload is malformed or the endpoint is down
Twenty-nine POST requests, manually routed, results manually transcribed. For a test suite that will be repeated every release cycle.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the endpoint URLs and request bodies, sends each POST request through Scrape.do's proxy infrastructure, and writes the HTTP status code and response body back into columns C and D — row by row.
For each row in this sheet, send a POST request to the URL in column A with the JSON body in column B using Scrape.do, and write the HTTP status code and response into columns C and D.
What You Get
- Column C: HTTP status code for each request (200, 201, 422, 500, etc.)
- Column D: the response body as returned — JSON string, error message, or empty if the endpoint returned no body
- Rows where the POST itself fails (network error, timeout) write a descriptive error label into column C
- All requests route through Scrape.do's proxy so originating IP varies per request by default
What If the Data Is Not Quite Ready
Request bodies in column B are stored as text strings but contain single quotes instead of valid JSON
Before sending, convert each value in column B from single-quoted to double-quoted JSON format to ensure valid payloads. Then send a POST request to each URL in column A with the corrected body via Scrape.do and write the status code and response into columns C and D.
You want to target a specific geo-region for all requests
For each row, send a POST request to the URL in column A with the body in column B through Scrape.do, geo-targeted to DE. Write the HTTP status code into column C and the response body into column D.
You only want to send requests where column E marks the row as active
Send POST requests only to rows where column E says "active". For each active row, use Scrape.do to POST to the URL in column A with the body in column B. Write the status code into column C and the response into column D.
Full test pipeline in one shot
Filter to rows where column E says "active". For each active row, validate that column B contains valid JSON — if not, write "Invalid payload" in column C and skip. For valid rows, send a POST request to column A with the column B body via Scrape.do geo-targeted to DE. Write the HTTP status code into column C, the response body into column D, and a pass/fail label into column E based on whether the status code is 200 or 201.
Filtering, payload validation, geo-targeted POST, and result classification — one prompt covers the whole test cycle.
Try It
Get the 7-day free trial of SheetXAI and open the Google Sheet with your endpoint list and request bodies, then ask it to send the POST requests and populate the response columns. See also the spoke on async batch scraping for large endpoint sets, or the hub overview for all Scrape.do workflows.