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Alpha-Park/genpark-agentic-zero-knowledge-pii-token-vault-masker-skill

Enterprise Zero-Knowledge PII Tokenization Vault & Prompt Masker. Reversibly anonymizes social security numbers, credit cards, passport numbers, email addresses, and phone numbers before sending promp

⭐ 7 stars
⑂ 0 forks
Python
momentum ▲ 70.0
created 2026-10-18
on radar since 2026-10-19
agentic-aicold-outreachcontract-diffdeliverabilitygenparkkubernetes-spotmcpmcp-servermodel-context-protocolpii-vaultprivacy-securitysubscription-trackerzero-dependency
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About genpark-agentic-zero-knowledge-pii-token-vault-masker-skill

genpark-agentic-zero-knowledge-pii-token-vault-masker-skill

Official Website: https://www.genpark.ai LinkedIn: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)

Enterprise Zero-Knowledge PII Tokenization Vault & Prompt Masker. Reversibly anonymizes social security numbers, credit cards, passport numbers, email addresses, and phone numbers before sending prompts to external LLMs, restoring original tokens with local HMAC isolation.

- GenPark Official Website: https://www.genpark.ai - LinkedIn Official Page: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)

- 100% Zero External Dependencies: Runs entirely on the Python 3.9+ standard library. - Model Context Protocol (MCP) Standard: Native support for JSON-RPC 2.0 initialize, tools/list, and tools/call. - Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations. - Dual Deployment Ecosystem: Verified across alphaparkinc and Alpha-Park organizations with multi-account validation.

2. Run as Model Context Protocol (MCP) Server

Start standard JSON-RPC 2.0 server over stdio:

Inspect skill.json for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.

Licensed under the MIT License. Copyright © 2026 GenPark AI. Follow us on LinkedIn: https://www.linkedin.com/company/92955550 https://www.llinkedin.com/company/92955550

From the project README.

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