Enterprise Knowledge Graph Provenance & Anti-Hallucination Tracer (inspired by Tencent Docs, Meeting & Enterprise Knowledge Bases). Provides cryptographic chunk hashing, reverse claim-to-source attrib
genpark-enterprise-knowledge-graph-provenance-tracer-skill
Production-Grade Real-Time Sensory Grounding & Enterprise Managed Agent Lifecycle Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)
🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation
genpark-enterprise-knowledge-graph-provenance-tracer-skill provides industrial-grade capabilities engineered for next-generation Personal Multimodal Agents 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 Knowledge Graph Provenance & Anti-Hallucination Tracer (inspired by Tencent Docs, Meeting & Enterprise Knowledge Bases). Provides cryptographic chunk hashing, reverse claim-to-source attribution, clearance boundary validation, and provenance audit trails.
- Zero-Dependency Architecture: Runs anywhere Python 3.9+ is installed without pip install overhead or supply-chain vulnerabilities. - Model Context Protocol (MCP) First: Fully compatible with Claude Desktop, Cursor, GenPark Engine, Meta Muse, Ray-Ban smart glasses, and enterprise agent runtimes. - Deterministic & Safe: Structured JSON schemas, cryptographic verification, rigorous boundary validation, and real-time telemetry. - High Concurrency & Low Latency: In-memory caching, vectorized math approximations, and robust fault-tolerant state handling.
From the project README.
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