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eu-pii-redact

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eu-pii-redact

Redact European personal data (names, national IDs, IBANs, emails, phones) before it reaches an LLM, and restore it afterwards. Python client and MCP server.

pipPyPI
Version
0.1.0
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eu-pii-redact

Keep European personal data out of LLM prompts and logs, and put it back in the answer. Python client, LangChain integration and MCP server for the EU PII Redaction API.

Hi, my name is Karina Dahl. I was charged twice for order 88412.
Please refund to DK50 0040 0440 1162 43 or call me on +45 32 12 34 56.
Karina

becomes

Hi, my name is [PERSON_1]. I was charged twice for order 88412.
Please refund to [IBAN_1] or call me on [PHONE_1].
[PERSON_1]
  • Names from evidence, not capital letters: titles, greetings, roles, Name: labels, sign-offs, or a first name from 140,000 European names. "Best Practices" and "Court of Justice" stay as they are.
  • National ID numbers from 21 EU/EEA countries, checked by check digit and birth date (personnummer, HETU, DNI/NIE, codice fiscale, NIR, PESEL, BSN, CPR, ...).
  • IBANs (mod-97), cards (Luhn), EU VAT numbers, emails, phones (with + prefix), IPs.
  • Every mention of a person shares one placeholder; order and invoice numbers stay untouched.

You need a RapidAPI key with a plan for the API. The free plan gives 500 requests a month. Set it as RAPIDAPI_KEY.

Python

pip install eu-pii-redact
from eu_pii_redact import Redactor

with Redactor() as r:                       # reads RAPIDAPI_KEY
    redaction = r.redact(ticket)
    reply = ask_llm(redaction.text)         # the model only sees placeholders
    print(redaction.restore(reply))         # real values back in the answer

redaction.entities lists each finding with its type, offsets in the original text and placeholder (national IDs also carry country and scheme). Texts longer than 50,000 characters are sent in pieces with consistent placeholders. r.redact(text, types=["EMAIL", "IBAN"], mode="mask") masks with asterisks.

LangChain

pip install "eu-pii-redact[langchain]"
from eu_pii_redact.langchain import protect, PIIRedactionTransformer

safe_llm = protect(llm)   # any model or chain that takes a string
safe_llm.invoke("Draft a reply to Karina Dahl about her refund to DK50 0040 0440 1162 43")
# the model sees [PERSON_1] and [IBAN_1]; the returned message has the real values again

docs = PIIRedactionTransformer().transform_documents(docs)   # e.g. before indexing for RAG

MCP server

Lets an AI assistant redact text and, more importantly, files without reading them: redact_file reads and writes the file itself and only reports counts, so the personal data never enters the conversation. restore_file puts the values back locally.

ToolWhat it does
redact_textRedact a text; returns the redacted text and entities (no original values)
redact_fileRedact a UTF-8 file into a new file; writes a restore mapping (owner-only permissions)
restore_filePut the original values back into a file using that mapping, offline

Claude Code

claude mcp add eu-pii-redact -e RAPIDAPI_KEY=your-key -- uvx eu-pii-redact

Claude Desktop / Cursor / other hosts (mcpServers config)

{
  "mcpServers": {
    "eu-pii-redact": {
      "command": "uvx",
      "args": ["eu-pii-redact"],
      "env": { "RAPIDAPI_KEY": "your-key" }
    }
  }
}

Limits

Rule-based, which keeps it fast (about 0.1 s for 50,000 characters) and predictable: no street addresses yet, phone numbers need an international prefix, and a name without any cue whose surname is an English word ("Will Smith") is missed on purpose. Use it as a strong first layer, not as a compliance guarantee.

License

MIT for this client package. The API itself is a hosted service.

Keywords

anonymization

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