obsify
Related Servers
Alternatives to obsify
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceLet LLMs analyze sensitive data safely by querying a tokenized, join-preserving copy of the database, with fail-closed PII scanning and provable numeric equivalence.MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to access only task-relevant data with secrets hidden and personal details pseudonymized, while enforcing destination policies to prevent data leakage even under prompt injection.Apache 2.0
- AlicenseAqualityBmaintenanceSelf-hosted governance layer between an AI assistant and your data: allow/deny policy, deterministic PII masking, row caps, and a hash-chained audit log with an Ed25519-signed receipt for every access, verifiable offline.4341 npm3MIT
- AlicenseNot gradedqualityDmaintenanceActs as an anonymizing proxy between AI agents and databases, detecting PII and replacing it with realistic fake data so agents never see real data.Apache 2.0
- AlicenseAqualityBmaintenanceEnables safe interaction with cloud LLMs by redacting sensitive entities into reversible placeholders, enforcing deterministic egress policies with human approval, and rehydrating responses so real data never leaves the process.4MIT

Praxis Liteofficial
AlicenseAqualityBmaintenanceEnables AI agents to safely interact with local files by enforcing policies that allow, block, or require approval for actions, while protecting credentials and maintaining a tamper-proof audit log.122MIT
TDQS
Scored across 5 tools
Each tool has a clear, distinct purpose: make_synthetic_twin creates a fake dataset, run_on_real executes code against real data, scan_pii identifies PII locations, redact_text masks PII in text, and verify_value_free checks for forbidden terms. No two tools overlap in what they accomplish.
Most tools follow a verb_noun pattern (make_synthetic_twin, scan_pii, redact_text, verify_value_free), but run_on_real breaks the pattern with a prepositional phrase. The style is consistent (all snake_case, verbs first) but the deviation is noticeable.
With 5 tools, the count is well-scoped for a focused PII-handling server. Each tool covers a necessary step in the workflow, and the count is within the typical 3-15 range, though a few additional helpers could be justified (e.g., a check for twin accuracy).
The tool surface covers the core lifecycle: protect data (scan, redact, verify) and enable safe analysis (twin, run on real). Minor gaps exist, such as no tool to validate the synthetic twin's fidelity against the real file, and verify_value_free lacks a positive counterpart, but agents can work around these.