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402utils JSON-to-CSV Converter
x402
402utils JSON-to-CSV Converter is a paid API for AI agents from 402utils.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-12).
Converts a JSON array of objects into a properly formatted RFC 4180 CSV with configurable delimiter, column selection, and nested object flattening
Price / call$0.002
Success—
StatusUnknown
How this service works
Convert a JSON array of objects into a clean RFC 4180 CSV: header row, CRLF records, correct quoting and quote-doubling. Nested objects flatten to dot-notation columns (a.b.c), arrays are JSON-encoded into their cell, and you can select and order columns explicitly. Delimiter: comma, semicolon, tab or pipe. Caps: 100,000 rows, 5 MB body, 20 MB CSV out. Returns text/csv ready for Excel, Google Sheets or a data pipeline.
Output
Returns a text/csv response with an RFC 4180-compliant CSV: a header row with column names (dot-notation for nested fields), CRLF line endings, correct quoting and quote-doubling for special characters, and one row per input object. Arrays within objects are JSON-encoded into their cell; nulls become empty cells. Ready for direct import into Excel, Google Sheets, or a data pipeline.
Example use cases
Example prompt
“Convert this JSON array of order records into a CSV file using a semicolon delimiter, and only include the columns order_id, customer.name, and total_amount.”
Technical details
Endpoint
POSThttps://402utils.com/v1/json-to-csv?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to transform a JSON array of objects (including nested structures) into a standards-compliant CSV without writing custom serialization code. Ideal for data pipeline automation, generating spreadsheet downloads from API responses, or preparing structured exports for tools like Excel or Google Sheets. Prefer over manual conversion when nested objects need dot-notation flattening or when column ordering and selection matter.
Side effects
- Input array exceeds 100,000 rows — returns 400 or payload-too-large error
- Request body exceeds 5 MB — returns 413 or similar size error
- Output CSV would exceed 20 MB — returns an error indicating output size limit
- rows field is missing or empty — returns 400 validation error
- Invalid delimiter value (not comma, semicolon, tab, or pipe) — returns 400 validation error
- Malformed JSON body — returns 400 parse error
- columns array references names that produce no matches — returns CSV with empty cells but no error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | 1–100,000 plain JSON objects, one per CSV record. Nested objects flatten to dot-notation column names; arrays are JSON-encoded into their cell; null becomes an empty cell. |
| columns | array | Optional column selection and order (flattened dot-notation names). Unknown names produce empty cells. Omit to use the union of all flattened row keys in first-seen order. |
| delimiter | string | Field separator. |
Output
Schema · Response
{
"type": "json",
"example": "name,city,stats.score,stats.active,tags\r\nJeanne d'Arc,Orléans,9.5,true,\r\nJosé,,,,\"[\"\"vip\"\",\"\"beta\"\"]\"\r\n"
}Tags
x402
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