knowledge-ops

Multi-layer ingestion and cross-source synchronization consolidate local files and MCP memory into a single knowledge base. The system routes incoming data to appropriate storage layers, generating indexes for fast retrieval across durable Git-backed repositories.

To avoid duplicate entries during knowledge ingestion, the system searches existing storage layers before writing. It automatically checks for existing facts and updates entries across the MCP knowledge graph, preventing scattered or duplicated information.

Yes, GitHub functions as a durable backend for semantic search. The system leverages durable Git-backed repositories for cross-session storage, enabling structured knowledge graph retrieval and relationship mapping across indexed workspace memories.

Knowledge base synchronization works with vector and graph stores. The system classifies incoming knowledge, routes it to appropriate storage layers, and applies semantic graph creation to enable consistent cross-session retrieval and indexing.

To query what the system knows about a specific topic, use semantic retrieval via MCP. The structured knowledge graph maps relationships across stored memories, answering "what do we know about X" consistently across local files and durable repositories.

Apply redaction and safety quality gates during knowledge ingestion before indexing updates. The system enforces these gates during multi-layer storage routing, ensuring sensitive information is redacted before entering the durable knowledge base.