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Add DLP protection, redaction, blocking, and audit logs to AI document access.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-dlp" yet — see the docs or source repo.
Connect mcp-dlp to my AI assistant so it scans company knowledge-base documents before reading them for ID numbers, phone numbers, emails, API keys, and contract values; redact matched fields, block high-risk content, and keep audit logs.
A DLP interception and redaction plan with sensitive-data detection, blocking rules, and audit logging requirements.
I am building a support AI. Use mcp-dlp to restrict the model from reading personal data in ticket attachments, such as names, addresses, bank card numbers, and ID numbers; allow issue summaries, but do not expose raw sensitive content.
A privacy protection rule set for support attachments that ensures the model only receives redacted, usable information.
Design an internal AI document access control workflow using mcp-dlp: when employees query documents through AI, the system should record access time, matched files, sensitive data types, action taken (allow, redact, or block), and operator identity for compliance audits.
An access control and logging design tailored for compliance auditing.
Provide controlled repository access for AI coding agents with redaction and audit logs.
Inspect and configure Chrome Enterprise security, telemetry, and licensing via AI agents.
Sanitize documents locally by removing or transforming PII before public LLM use.
Analyze AI security, scan vulnerabilities, and monitor code leaks efficiently.
Audit MCP configs for exposed access, secrets, models, and compliance AI-BOMs.
Automatically scans and blocks malicious MCP traffic across popular AI desktop apps.