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Vextorium CSV Cleaner & Normalizer
x402
Vextorium CSV Cleaner & Normalizer is a paid API for AI agents from api.vextorium.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-01).
Cleans and normalizes raw CSV data in-memory, returning structured JSON with normalized column names, inferred types, deduplicated rows, and a changelog of applied transformations.
Price / call$0.02
Success—
StatusUnknown
How this service works
CSV cleaning and normalization to JSON: column names, types, duplicates and empty values. Data is processed in memory and not stored.
Output
Returns a JSON object with: 'datos' (array of cleaned row objects with normalized column names as keys), 'filas' (number of rows after cleaning), 'columnas' (list of normalized column names), 'cambios_aplicados' (array of strings describing each transformation applied), and 'aviso_privacidad' (privacy notice confirming data is not stored).
Example use cases
Cleaning a dirty spreadsheet export
“I exported this CSV from our CRM and it's a mess — duplicate rows, inconsistent column names, and missing values all over the place. Can you clean it up and give me back the data as JSON? Here's the raw CSV: 'customer_name,AGE,Email Address\nJane Doe,34,jane@acme.com\nJane Doe,34,jane@acme.com\nJohn,,john@acme.com'”
ETL pipeline data normalization
“Before I load this CSV into our database, I need it cleaned and normalized into JSON — fix the column names, drop duplicates, infer proper data types, and tell me what changes were made. Here's the CSV: 'Product Name,Price ,Qty,Category\nWidget A,9.99,10,tools\nWidget A,9.99,10,tools\nGadget B,,5,electronics'”
Validating user-uploaded CSV files
“A user just uploaded this CSV file to our platform and I need to validate and clean it before processing — normalize the headers, remove empty rows, deduplicate, and return it as a JSON array so I can work with it programmatically. Raw CSV: 'First Name,Last Name ,email,Phone Number\nMaria,Garcia,maria@email.com,555-1234\n,Smith,smith@email.com,555-5678\nMaria,Garcia,maria@email.com,555-1234'”
Technical details
Endpoint
POSThttps://api.vextorium.com/limpiar-datos-pago?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, in-memory CSV cleaning and JSON conversion without storing data — ideal for ETL preprocessing, validating user-uploaded CSVs before ingestion, or normalizing spreadsheet exports before further processing. It is especially useful when you need a changelog of applied transformations (duplicates removed, empty values handled, column names normalized) returned alongside the clean data.
Side effects
- Malformed or non-parseable CSV input returns an error — input must be valid CSV text
- Missing required fields (input, from, to) cause a 400-level validation error
- Very large CSV payloads may time out or hit memory limits
- Passing non-CSV data in the 'input' field when 'from' is set to 'csv' will produce empty or erroneous output
- Incorrect bodyType specification may cause parsing failures
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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