# genpark-enterprise-compliance-data-retention-gdpr-erasure-sentinel-skill

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

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## 🌐 Official GenPark AI Ecosystem Links

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

---

## 🌟 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`, 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.

---

## 🚀 Quick Start

### 1. Direct Python SDK Usage

```python
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`:

```bash
python mcp_server.py
```

Execute embedded test harness:

```bash
python mcp_server.py --test
```

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## 🛠️ MCP Tool Specification

Inspect [`skill.json`](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](LICENSE). Copyright © 2026 [GenPark AI](https://www.genpark.ai).
Follow us on LinkedIn: [https://www.linkedin.com/company/92955550](https://www.linkedin.com/company/92955550) | [https://www.llinkedin.com/company/92955550](https://www.llinkedin.com/company/92955550)