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Detect and mask sensitive data with flexible rules and masking strategies.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "sensitive-info-mcp" yet — see the docs or source repo.
Scan this application log for sensitive information, detect emails, phone numbers, national IDs, bank card numbers, and API keys, then replace them with masked versions while preserving the original text structure.
Returns a redacted log text and identifies the types of sensitive data found.
Review this exported customer dataset, find possible names, emails, addresses, phone numbers, and account identifiers, then apply hashing, replacement, or full redaction by field type to produce a safely shareable version.
Outputs an anonymized dataset suitable for external sharing and explains the masking method used for each field type.
Run sensitive information detection on these prompts and knowledge base snippets before sending them to an LLM, using both rule-based matching and semantic detection to find potential leaks, then fully redact high-risk content and partially mask low-risk content.
Returns the reviewed safe text along with risk notes and handling results for each segment.
Detect and redact sensitive personal information from files safely and quickly.
Detect, redact, and audit PHI in medical text before AI use.
Give coding agents redacted access to private local files and context.
Sanitize documents locally by removing or transforming PII before public LLM use.
Provide controlled repository access for AI coding agents with redaction and audit logs.
Monitor AI inputs and outputs to block injections, leaks, and phishing.