Persists project context and learnings across Claude sessions using semantic search and atomic fact storage.
This skill integrates the Model Context Protocol (MCP) Memory Server into Claude Code, allowing the AI to maintain a persistent knowledge base across different sessions and projects. It provides a structured way to store atomic facts, search past learnings through semantic queries, and recall information using natural language time references. By bridging the context gap between tasks, it ensures that architectural decisions, unique project constraints, and specific developer preferences are never lost, making Claude a more effective long-term partner in the development lifecycle.
Key Features
01Natural language time queries for historical recall
02Atomic fact storage to ensure high-precision search results
033 GitHub stars
04Tag-based organization for project-specific facts
05Cross-session persistence of project-specific learnings
06Semantic search for content-based memory retrieval
Use Cases
01Maintaining a consistent list of coding standards across multiple repositories
02Recalling complex architectural decisions made in previous weeks
03Building a searchable repository of project-specific constraints and edge cases
