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CSV Data Cleanup & Normalization
x402
CSV Data Cleanup & Normalization is a paid API for AI agents from well-016-datacleanup.rainmaker-wells.workers.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-22).
Cleans and normalizes a CSV file by trimming whitespace, standardizing dates, emails, and phone numbers, and detecting/merging duplicate rows — returning cleaned CSV plus a JSON report
Price / call$0.005
Success—
StatusUnknown
How this service works
Clean a CSV ($0.005 USDC): give an https url or inline csv (max 1 MB / 20k rows). Trims whitespace, optional case rules, dates to ISO 8601, lowercases emails, normalizes phone digits, merges or flags exact + fuzzy duplicate rows on key_columns. Returns cleaned CSV text + JSON report (rows in/out, dupes, columns changed). Deterministic, no AI. As is, no warranty. Nothing stored.
Output
Returns the cleaned CSV as text with all normalizations applied, plus a JSON report containing: total rows in, rows out after deduplication, number of duplicate rows found, and a list of which columns were changed.
Example use cases
Pre-import CRM data cleanup
“I have a CSV export of our CRM contacts at https://example.com/crm_export.csv — can you clean it up before we import it? Trim all whitespace, standardize the phone numbers, lowercase emails, convert any dates to ISO 8601, and merge exact duplicate rows matching on the 'email' column.”
Deduplicating a marketing list
“We have a marketing list CSV pasted here with about 5,000 rows — can you find and remove duplicate contacts using 'email' and 'last_name' as the key columns, and give me a report of how many dupes were removed?”
Normalizing survey response exports
“I exported survey responses as a CSV and the formatting is all over the place — dates in different formats, phone numbers with random characters, inconsistent capitalization. Can you normalize everything: ISO dates, clean phone digits, lowercase emails, and trim any extra spaces?”
Technical details
Endpoint
POSThttps://well-016-datacleanup.rainmaker-wells.workers.dev/mcp?utm_source=zero.xyz#data-cleanup#data-cleanupWhen to prefer
Use this endpoint when you need a deterministic, rule-based CSV cleaning pipeline — not AI-based transformation — that handles whitespace trimming, date/phone/email normalization, and exact or fuzzy duplicate detection in a single call for $0.005 USDC. Prefer this over manual ETL scripts or AI-based data cleaning when you need reproducible, auditable transformations on files up to 1 MB / 20k rows with no data retention.
Side effects
- CSV exceeds 1 MB or 20,000 rows — request rejected
- Invalid or inaccessible URL provided — fetch failure
- Malformed CSV that cannot be parsed — error returned
- Key columns specified for deduplication not found in CSV headers
- Network timeout fetching remote CSV URL
Tags
x402
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