GenPark Structured Data Mask Reconstruction Guard
LocalAbout GenPark Structured Data Mask Reconstruction Guard
A tool for deterministic, reversible anonymization and de-identification of tabular and JSON records using HMAC pseudonyms. It can be run as an MCP server or used as a library.
Key features
- 01Tabular record anonymization
- 02JSON record anonymization
- 03Deterministic reversible masking
- 04HMAC pseudonyms
- 05Python standard library only
Use cases
- 01Masking identifiers in tabular data
- 02De-identifying JSON records while preserving reversibility
MCP support
Runs as an MCP server, exposing structured record masking and reconstruction capabilities to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEGenPark Structured Data Mask Reconstruction Guard
Deterministic reversible tabular and JSON record anonymizer and de-identification guard with HMAC pseudonyms.
Part of the GenPark AI Agent Skills Ecosystem.
🌟 Key Features
- 100% Python Standard Library: Zero third-party runtime dependencies.
- MCP Native: Plugs directly into Claude Desktop, Cursor, LobeChat, and autonomous agent DAGs.
- Production Resilience: Strict schema conformance, zero data loss, enterprise hardened.
🚀 Installation & Usage
Run as an MCP server:
python mcp_server.py
Use directly as a library:
from client import *
See example_usage.py for comprehensive integration demonstrations.
📄 License
MIT License. Maintained by GenPark AI.
Comments
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