I'm Zackery, a solo dev. I got frustrated with the current state of LLM memory (mostly just dumping embeddings into a vector DB and doing a top-K semantic search). It feels like a filing cabinet, not a brain. I built Mnemosyne as a local, associative memory backend that plugs directly into Claude Desktop, Cursor, and Windsurf via the Model Context Protocol (MCP). Instead of standard RAG, it uses a SQLite graph with spreading activation and Hebbian decay. How it works: It uses SQLite FTS5 for the initial retrieval (BM25). It then performs a Breadth-First Search (BFS) across a localized graph of edges to spread activation energy to related concepts. Memories that are frequently co-retrieved form stronger edges (LTP). Unused trivia naturally decays over time. It's a single, standalone binary (C#/.NET 8 AOT compiled) for Windows and Linux that runs entirely locally. Zero cloud dependencies. Your data never leaves your machine.…