Enterprise Compliance Data Retention GDPR Erasure Sentinel
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
genpark-enterprise-compliance-data-retention-gdpr-erasure-sentinel-skill
Official Website: https://www.genpark.ai
LinkedIn: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
Enterprise Work Agent GDPR Right-to-be-Forgotten & CCPA Erasure Sentinel. Audits distributed data stores (relational DBs, vector embeddings, activity logs), checks legal hold exemptions, executes cascading pseudo-anonymization, and anchors cryptographic HMAC-SHA256 Proofs of Erasure.
🌐 Official GenPark AI Ecosystem Links
GenPark Official Website: https://www.genpark.ai
LinkedIn Official Page: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
Related MCP server: mcp-privacy-shield
🌟 Key Features
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, andtools/call.Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
Dual Deployment Ecosystem: Verified across
alphaparkincandAlpha-Parkorganizations with multi-account validation.
🚀 Quick Start
1. Direct Python SDK Usage
from client import EnterpriseComplianceDataRetentionErasureSentinel
def main():
sentinel = EnterpriseComplianceDataRetentionErasureSentinel()
stores = [
{"store_name": "customer_relational_db", "records_count": 25},
{"store_name": "vector_embedding_store", "records_count": 120},
{"store_name": "analytics_event_logs", "records_count": 450}
]
res = sentinel.execute_gdpr_erasure_workflow("CUST-EU-8821", stores)
print("--- Enterprise GDPR Erasure Audit Output ---")
print(f"Subject: {res['data_subject_id']} | Status: {res['erasure_status']}")
print(f"Records Scrubbed: {res['total_records_scrubbed']}")
print(f"Proof Certificate: {res['proof_certificate']['certificate_id']}")
print(f"HMAC Digest: {res['proof_certificate']['hmac_sha256_proof'][:32]}...")
if __name__ == "__main__":
main()
2. Run as Model Context Protocol (MCP) Server
Start standard JSON-RPC 2.0 server over stdio:
python mcp_server.pyExecute embedded test harness:
python mcp_server.py --test🛠️ MCP Tool Specification
Inspect skill.json for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.
📜 License & Community
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
Tool Schema Changelog
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