scrubguard
OfficialRelated Servers
Alternatives to scrubguard
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceSanitizes text and files by removing PII, secrets, and custom patterns locally before sending to LLMs, with optional reverse-scrubbing.3303 npm124 PyPI2MIT
- FlicenseNot gradedqualityBmaintenanceEnables agents to encrypt and sanitize sensitive data such as credentials, credit card numbers, and addresses locally before dispatching prompts to cloud LLMs, then rehydrate the masked values client-side. It runs deterministically with zero external dependencies over MCP JSON-RPC stdio, so no plaintext PII leaves the user's machine.7-
- FlicenseNot gradedqualityBmaintenanceEnables local zero-knowledge encryption of a personal vault and sanitization of PII such as credentials, credit cards, and addresses before dispatch to cloud LLMs, with client-side rehydration of masked data.7-
- AlicenseNot gradedqualityCmaintenanceEnables deterministic, no-LLM scrubbing of secrets from text or logs before they enter agent context, supporting redaction, masking, and hashing without ever leaking the original value.33 PyPIMIT
- AlicenseAqualityAmaintenanceEnables an AI assistant to redact text and, more importantly, files without reading them, since file redaction and restoration happen locally and only counts are reported, keeping personal data out of the conversation. It exposes tools for redacting text, writing a redacted copy of a UTF-8 file with an owner-only restore mapping, and putting original values back offline.3MIT
- AlicenseAqualityAmaintenanceEnables agents to detect and redact PII and secrets in text, HTML, and PDF documents before they reach an LLM, with reversible placeholder, mask, or hash redaction, and to list supported detectors and redaction styles.4MIT
TDQS
Scored across 3 tools
Each tool targets a distinct operation and input type: scrubbing free text, rehydrating tokenized text, and scrubbing structured JSON. The descriptions make the text-vs-JSON and forward-vs-reverse boundaries unambiguous, so misselection is unlikely.
All three tools follow a strict verb_noun snake_case pattern (scrub_text, rehydrate_text, scrub_json), with the verb signaling direction (scrub vs rehydrate) and the noun signaling the target (text vs json). Fully predictable.
Three tools is lean but each earns its place for a focused PII-scrubbing utility; there is no filler. The surface is on the small side, but the scoping is deliberate rather than thin.
The core scrub/rehydrate lifecycle is covered for text and scrubbing is covered for JSON, so primary workflows are complete. Minor gaps remain: there is no rehydrate_json counterpart for restoring tokens in structured data, and no way to inspect or manage the vault map.