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PII & Secret Redactor

PII & Secret Redactor

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github.com/tylerscomic-labSecurity0Updated 4w ago
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About PII & Secret Redactor

An MCP server for removing personal data and credentials from text before it reaches an LLM, log or ticket. It verifies many detected values with checksums and supports reversible placeholders, while noting that pattern-based detection is not a compliance guarantee.

Key features

  1. 01Checksum-verified financial identifiers
  2. 02Contact, identity and IP detection
  3. 03Cloud and service key detection
  4. 04Mask, hash, remove or replace with tokens
  5. 05Restore originals from placeholders

Use cases

  1. 01Redact customer data before an LLM request
  2. 02Remove credentials from logs or support tickets
  3. 03Restore original values in a model response

MCP support

Exposes PII detection, text redaction, restoration and detector-listing tools to MCP clients.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://pii-redactor-mcp.mcpize.run/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

PII & Secret Redactor

Redact PII and secrets from text before it reaches an LLM. Checksum-verified cards, IBANs and routing numbers, SSN range rules, API keys, and reversible placeholders you can restore after the model responds.

Send the question, not the customer's data

Strip personal data and credentials out of text before it goes to a model, a log or a ticket, then put the originals back in the answer.

What it detects

  • Verified, not just matched: credit cards (Luhn, brand identified), IBANs (mod-97), US routing numbers (ABA checksum), SSNs (invalid ranges rejected). Order numbers and random digit strings are left alone.
  • Contact and identity: emails, phone numbers (US and international), labelled dates of birth, US street addresses, IPv4 and IPv6.
  • Secrets: Anthropic, OpenAI, AWS, GitHub, Stripe, Slack and Google keys, JWTs, private keys, database URLs with credentials.

Tools

  • detect_pii: findings with type, position and a masked preview. Never echoes full values.
  • redact_text: placeholder (stable tokens like <EMAIL_1>, same value gives the same token), mask, salted hash, or remove.
  • restore_text: swap placeholders back to the originals in the model's response, using the mapping you keep.
  • list_detectors: exactly what is and is not covered.

Be clear about the limits

Pattern and checksum based. It does not detect personal names or free-form addresses in other formats, so it reduces exposure but is not a compliance guarantee for HIPAA, GDPR or PCI. Input is processed in memory and never stored or logged.

Use it

Hosted on MCPize with a free tier (10 calls a day). Remote MCP endpoint (streamable HTTP, API key from MCPize):

https://pii-redactor-mcp.mcpize.run/mcp

Or run it yourself:

npm install
node server.js   # listens on :8080, MCP at /mcp

MIT licensed.

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