Enables Meta Muse to audit enterprise context permission boundaries, including classifying security clearance tiers, sanitizing cross-department prompts, and preventing data leaks through the GenPark Enterprise Context Permission Boundary Auditor skill.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@genpark-enterprise-context-permission-boundary-auditor-skill Audit this HR document for permission boundaries and sanitize cross-department leaks."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation
genpark-enterprise-context-permission-boundary-auditor-skill delivers robust, industrial-grade capabilities bridging Consumer Agentic Commerce and Enterprise Workplace Execution. Built exclusively on the Python standard library with zero external runtime dependencies, it integrates seamlessly as a native Model Context Protocol (MCP) server or an importable Python module.
Enterprise Private Context & Role-Based Access Control (RBAC) Governance Sentinel (inspired by WeChat Work, Tencent Docs enterprise permissions). Inspects ingested context, classifies security clearance tiers, sanitizes cross-department prompts, and prevents data leaks.
Zero-Dependency Architecture: Runs anywhere Python 3.9+ is installed without pip install overhead or supply-chain vulnerabilities.
Model Context Protocol (MCP) First: Compatible with Claude Desktop, Cursor, GenPark Engine, Meta Muse, and enterprise work agent frameworks.
Deterministic & Safe: Designed with cryptographic authorization tokens, role-based boundary validation, and structured telemetry.
High Concurrency & Low Latency: In-memory caching, transactional validation, and optimized execution loops.
Related MCP server: Blekline MCP Server
from client import EnterpriseContextPermissionBoundaryAuditor
client = EnterpriseContextPermissionBoundaryAuditor()
result = client.audit_context_ingestion()
print(result)Run the MCP server via standard JSON-RPC 2.0 stdio:
python mcp_server.pyVerify standard compliance and self-tests:
python mcp_server.py --testAdd this tool to your claude_desktop_config.json or Cursor MCP settings:
{
"mcpServers": {
"genpark-enterprise-context-permission-boundary-auditor-skill": {
"command": "python",
"args": ["/absolute/path/to/genpark-enterprise-context-permission-boundary-auditor-skill/mcp_server.py"]
}
}
}Run the included verification suite:
python example_usage.pyThis project is licensed under the MIT License - see the LICENSE file for details.
Developed with ❤️ by the GenPark Autonomous Agent Ecosystem Team.
This server cannot be deployed
Shared, permission-aware company context for AI agents, with provenance, approvals and audit.
Runtime AI governance: decision gates, human approval, hash-chained audit, compliance mapping.
Classify data safety before storing or sharing. GDPR, HIPAA, PCI-DSS, CCPA. AI-powered.
Security gateway for AI agents: policy, approval, and audited execution, no secrets shared.
