The Scenario
You're an ops engineer and a customer data audit revealed that 200 Nango connections are missing their customer segment labels and environment identifiers. The data lives in a spreadsheet — connection ID in column A, the environment tag in column B, the customer tier in column C. Whoever set up these connections initially didn't set the metadata, and now the platform's filtering logic can't group them correctly.
Your job is to patch all 200 of them before the next billing cycle closes.
The bad version:
- Write a script that reads the sheet, builds the metadata payload for each row, and makes a PATCH request to the Nango update connection metadata endpoint
- Run the script, get 23 errors because some connection IDs in the sheet have trailing spaces or were deleted months ago and no longer exist in Nango
- Fix the script, re-run, and now you're unsure which of the 23 failed rows were already updated by the first pass and which ones weren't
An ops task that should take an hour has become a debugging session spanning two working days.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads your rows and talks to Nango directly. Launch the SheetXAI sidebar and give it this prompt.
For each row in my sheet with a connection_id in column A and metadata JSON in column B, update that Nango connection's metadata and write the update status in column C
What You Get
- SheetXAI iterates every row in sequence
- For each row: sends a metadata update request to Nango for the specified connection ID
- Column C receives SUCCESS for rows that update cleanly, ERROR with a reason for rows that fail (connection not found, invalid payload, etc.)
- No silent skips — every row gets a status, every error surfaces immediately
What If the Data Is Not Quite Ready
The metadata isn't in JSON format yet — it's split across multiple columns
For each row in my sheet with a connection_id in column A, environment tag in column B, and customer tier in column C, construct a metadata object from those values and update the Nango connection's metadata — write the update status in column D
Some connection IDs in the sheet may no longer exist in Nango and should be flagged before patching
For each row in my sheet, first check if the connection_id in column A exists in Nango — if not, write NOT FOUND in column D and skip the update; for connections that exist, apply the metadata from column B and write SUCCESS or ERROR in column D
Rows flagged as HIGH TIER need a different metadata structure than standard rows
For each row in my sheet, if column C says HIGH TIER, update the Nango connection metadata with priority set to high and the tag from column B; for all other rows, update with priority set to standard and the tag from column B — write the result in column D for each row
Validate all connection IDs, skip missing ones, apply tiered metadata logic, and write a summary of how many updates succeeded and how many failed
Check each connection_id in column A against Nango — write NOT FOUND in column D for any missing; for existing connections apply metadata using column B for the tag and column C for the tier with appropriate priority values; write SUCCESS or ERROR in column D; then below the data write the total count updated successfully and the total count that errored or were not found
One prompt, full coverage, no second pass needed.
Try It
Get the 7-day free trial of SheetXAI and open the Google Sheet with your connection IDs and metadata values, then ask it to push the updates to Nango. After patching, you can export the full connection inventory to verify the metadata applied correctly across all 200 rows.