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PII Anonymizer RGPD MCP
x402
PII Anonymizer RGPD MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.06/call, status unknown (last checked 2026-09-15).
Detects and anonymizes personally identifiable information (PII) in text to comply with GDPR/RGPD data protection regulations
Price / call$0.06
Success—
StatusUnknown
How this service works
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Output
Returns the input text with all detected personally identifiable information (PII) replaced or redacted — names, email addresses, phone numbers, dates of birth, physical addresses, and other GDPR-sensitive identifiers are anonymized, leaving the semantic structure of the text intact while removing privacy-sensitive content.
Example use cases
GDPR-compliant log sanitization
“I need to anonymize this server log before sharing it with our analytics team — it contains user emails and IP addresses: 'User alice@company.com (IP 192.168.1.42) logged in at 09:15 on 2024-03-12'. Please strip all the personal data.”
Customer support transcript redaction
“Before we store this support chat transcript in our data warehouse, can you remove all PII to make it RGPD compliant? Here's the text: 'Customer Marie Dupont, born 15/06/1985, living at 14 rue de la Paix Paris, called about her account FR7612345678901234567890189.'”
Dataset anonymization for ML training
“I have a batch of user-submitted feedback I want to use for model training but I need to anonymize it first — can you remove names, contact details, and any other personal identifiers from this text: 'Feedback from Pierre Martin (pierre.martin@gmail.com): Great service but the delivery to 8 Bd Haussmann 75009 Paris was late.'”
Technical details
Endpoint
POSThttps://api.m2mcent.com/pii-anonymizer-rgpd-mcp/api/processWhen to prefer
Choose this endpoint when you need automated GDPR/RGPD-compliant PII removal from free-form text strings, especially in European regulatory contexts. It is well-suited for pre-processing user data before storage, sharing logs with third parties, or preparing training datasets. Prefer it over manual redaction or generic text-transformation tools when regulatory compliance (RGPD framing) and speed are both priorities.
Side effects
- Empty or null data field returns an error
- Extremely long text strings may exceed processing limits
- Ambiguous context may cause under-detection of PII (false negatives)
- Text in unusual languages or encodings may reduce detection accuracy
- Structured data formats (JSON, CSV) embedded in text may not be fully parsed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| payload | string |
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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