MCP server for locally masking personal data in documents before sending them to a language model, then restoring the original data in the model's response.
An MCP server that enables LLMs to detect and anonymize over 25 types of Personally Identifiable Information (PII) using Microsoft Presidio. It supports various redaction strategies and can process both plain text and structured data to help ensure data privacy.
Local pseudonymisation MCP server that detects PII in text, replaces it with opaque tokens before sending to cloud LLMs, and restores tokens afterward.