cncf-storage-and-architecture

What problem does it solve?

This Skill addresses the need for a structured and flexible data persistence and architecture for the MCPAtlas project, ensuring maintainability and scalability.

Core Features & Use Cases

• Trait-based Storage: Implements interchangeable backend traits (GraphBackend, VectorBackend, CacheBackend) for different persistence needs.
• Data Pipeline Management: Defines a clear process for data ingestion, enrichment, and updates, including LLM integration.
• Service Layer Design: Outlines a clean separation of concerns with services depending on storage traits rather than concrete implementations.
• Use Case: When introducing a new database like SurrealDB for graph data or Qdrant for vector embeddings, this skill provides the architectural blueprint to integrate it seamlessly.

Quick Start

Configure the MCPAtlas to use SurrealDB for its graph backend.