Graph Memory
A personal knowledge graph for Claude that survives across sessions, devices, and tools. Built on Neo4j with semantic embeddings, OAuth-secured for use from Claude Code, Claude Desktop, and claude.ai web — all hitting the same graph.
https://github.com/user-attachments/assets/826e5f5a-5759-4b31-83dd-6bd7e0e044b8
Asked from my phone. Pulls a decision made days ago on my laptop, citing the commit hash.
No external API keys, no LLM provider integration, no per-token costs. Entity extraction runs inside your Claude sessions (Max plan). Embedding runs locally via bge-small-en. Everything stays on your hardware unless you choose to expose it.
Why a graph
Built-in memory in Claude Code is "append facts to markdown, grep later." That gets you 80% there but breaks at scale: no relationships, no confidence, no decay, no contradiction detection, no temporal awareness. Two memories that reinforce each other look identical to two memories that contradict each other.
This project replaces flat keyword matching with weighted, relationship-aware retrieval:
