Visual Issue Clustering

via “memory-visualization-with-graph-clustering”

** a lightweight, local RAG memory store to record, retrieve, update, delete, and visualize persistent "memories" across sessions—perfect for developers working with multiple AI coders (like Windsurf, Cursor, or Copilot) or anyone who wants their AI to actually remember them.

Unique: Implements clustering visualization as an MCP Prompt (guidance-oriented) rather than a tool, positioning it as a meta-cognitive aid for understanding memory organization rather than a direct operation

vs others: Lighter than full knowledge graph visualization systems (Neo4j, Gephi) by clustering on vector embeddings alone, avoiding entity extraction and relationship inference complexity while providing quick semantic insights

via “visual-issue-clustering”