by 24kchengYe
Give your AI agent a brain that remembers. Local memory system for Claude Code — 100% private, GPU-accelerated, zero cloud dependency.
# Add to your Claude Code skills
git clone https://github.com/24kchengYe/MemoMindLast scanned: 5/7/2026
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}Give your AI agent a brain that remembers.
A fully local, GPU-accelerated memory system for AI coding agents. Start building your digital twin's memory today — portable, evolving, and ready to migrate when a better system comes along.
AI memory has two audiences — the machine and the human. Most tools only address one:
| | For the AI (what it knows) | For the Human (what you can review) | |---|---|---| | Goal | AI remembers preferences, decisions, context across sessions | You browse, search, and manage conversation history | | Problem solved | "Why does it keep forgetting my coding style?" | "What did we discuss last Tuesday?" |
MemoMind handles the AI side — it gives your coding agent persistent, structured, intelligent memory. For the human side, see (our companion project for conversation history management).
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Use both together for the complete experience.
You've spent thousands of hours with AI — but it remembers nothing.
The problem isn't intelligence — GPT-5, Claude, Gemini are brilliant. The problem is amnesia. Every session is a blank slate. Every AI is an isolated silo. Your years of digital life produce zero compounding value.
What if your AI could remember everything? Not just this session — but every conversation you've ever had, every decision you've made, every day you've lived?
Claude Code already has CLAUDE.md and MEMORY.md. But they have fundamental limitations:
| | Claude Code Built-in | MemoMind |
|---|---|---|
| Storage | Plain Markdown files | PostgreSQL + pgvector + knowledge graph |
| Extraction | Manual — you write rules yourself | Automatic — LLM extracts facts from conversations |
| Retrieval | Full file loaded into context every time (wastes tokens) | 4-way hybrid search, only relevant memories recalled |
| Cross-session | Static rules; append-only notes | Dynamic knowledge graph with entity linking + temporal relationships |
| Reasoning | No — just loads text | reflect synthesizes insights across all memories |
| Scalability | Breaks down at ~200 lines (context bloat) | Handles thousands of memories efficiently |
They're complementary, not competing. CLAUDE.md is great for static project rules ("use tabs, not spaces"). MemoMind handles the dynamic knowledge that accumulates over time ("user tried Redis caching last week but switched to Memcached due to memory constraints").
MemoMind gives your AI a persistent, local, intelligent brain. Not a chat log — a living knowledge graph that grows with every interaction, every imported conversation, every day of your life.
| | Without MemoMind | With MemoMind |
|---|---|---|
| Session start | Blank slate, zero context | Recalls your preferences, past decisions, project context |
| 500 ChatGPT conversations | Scattered across browser tabs, unsearchable | Unified knowledge graph, every fact extracted and linked |
| 3 years of daily activities | Trapped in your planner app | Searchable timeline — AI knows your patterns and history |
| Cross-AI knowledge | ChatGPT doesn't know what you told Gemini | All conversations merged into one memory |
| Decision tracking | Lost when chat window closes | Stored as structured facts with source tracing |
| Cross-session reasoning | Impossible | reflect synthesizes insights across all memories |
| Privacy | Cloud-based, fragmented | 100% local — nothing leaves your machine |
You: "Let's use FastAPI instead of Express for this project"
Claude Code internally:
→ retain("Project migrating from Express to FastAPI") # auto-stores
Next week, new session:
→ recall("project tech stack") # auto-retrieves
→ "Based on your previous decision, I'll use FastAPI..."
You don't do anything — the AI handles it all.
| Metric | Value | |--------|-------| | Memory nodes | 50,100+ | | Knowledge links | 2,900,000+ | | Named entities | 4,600+ | | Time span | 2017 – present (9 years) | | AI chats imported | 541 (ChatGPT + Gemini) | | Life events imported | 5,500+ (2,400+ days) | | Knowledge Vault docs | 13,400+ (NoteDiscovery) | | Database size | ~500 MB | | Keyword search | 20–33ms | | Semantic recall | 235–430ms | | Daily LLM cost | < $0.01 |
One-click import your ChatGPT and Gemini conversation history into the knowledge graph — then trace any memory back to the original conversation.
Export your conversations using our companion tools, then import them into MemoMind. Every extracted memory links back to its source — click the 💬 icon on any memory card to view the full original conversation.
Companion tools for conversation export:
Import your daily activities from DayLife — every event becomes a searchable, AI-analyzable memory. Smart daily sync catches up automatically even if your computer was off for days.
Import once with import_daylife.py, then the daily sync keeps it updated forever. Combined with DayLife's CSV import feature, you can one-click visualize your entire life history — every plan, every achievement, every habit pattern — all searchable by AI.
| Feature | MemoMind | Mem0 | Graphiti/Zep | Letta | Cognee | Hindsight | |---------|----------|------|--------------|-------|--------|-----------| | GitHub Stars | — | 51K | 24K / 4K | 22K | 15K | 7K | | Funding | Self-funded | $24M (YC) | — | $10M | $7.5M | $3.5M | | Architecture | KG + pgvector | Vector + Graph | Temporal KG | Agent OS | ECL + KG | 4-network | | Retrieval | 4-way hybrid | Semantic + graph | Sem+BM25+graph | Agent-driven | 14 modes | 4 parallel | | Knowledge Graph | Built-in (pgvector) | Pro only ($249/mo) | Core (Neo4j) | No | Yes | Yes | | Temporal | Native | No | Bi-temporal | No | Partial | Yes | | Privacy | 100% local | Cloud default | Cloud/BYOC | Self-host opt | Local/Cloud | Local | | GPU Accel | Local CUDA | No | No | No | No | No | | LongMemEval | — | 49% | — | — | — | 91.4% | | Cost | $0.30