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Sanitize documents locally by removing or transforming PII before public LLM use.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Doc Sanitizer MCP Server" yet — see the docs or source repo.
Scan this contract locally, detect names, phone numbers, emails, ID numbers, and addresses, replace them with consistent placeholders, preserve the contract structure and clauses, and output a sanitized version safe for a public LLM.
A contract text with preserved meaning and format, but with personal sensitive data replaced.
Process these customer support chat logs, remove customer names, order numbers, contact details, and exact addresses, generalize personally identifiable information, and output data ready for sentiment analysis and issue categorization.
A batch of analysis-ready sanitized chat logs with sensitive fields removed or generalized.
Sanitize this interview transcript by identifying participant names, companies, locations, project codenames, and other sensitive details, replacing them with category labels while preserving contextual readability.
A sanitized interview transcript suitable for summarization and analysis with public models.
Detect and redact personally identifiable information in PDF documents.
Safely run any code in isolated Docker containers for testing and automation.
Secure LLM and MCP tool interactions with zero-trust controls and policy enforcement.
MCP tool for compliance automation, PII scanning, and audit tracking.
Create, edit, and format Word documents with tables, images, and footnotes via MCP.
Search official library docs and return clean text ready for LLM use.