Memoriki – LLM Wiki+MemPalace for persistent personal knowledge bases
Memoriki is a template for building personal knowledge bases where the LLM does all the maintenance work. It combines Karpathy's LLM Wiki pattern (structured markdown wiki maintained by an LLM) with MemPalace (an MCP server that adds semantic search and a temporal knowledge graph). Three layers: - Wiki pages with [[wiki-links]] and YAML frontmatter - the LLM creates and maintains these - Semantic search via embeddings (ChromaDB) - find things by meaning, not keywords - Knowledge graph with typed relationships and date validity - "what changed since last month?" It's not RAG. RAG re-derives…
What it does
In the maker’s words, at launch
Memoriki is a template for building personal knowledge bases where the LLM does all the maintenance work. It combines Karpathy's LLM Wiki pattern (structured markdown wiki maintained by an LLM) with MemPalace (an MCP server that adds semantic search and a temporal knowledge graph). Three layers: - Wiki pages with [[wiki-links]] and YAML frontmatter - the LLM creates and maintains these - Semantic search via embeddings (ChromaDB) - find things by meaning, not keywords - Knowledge graph with typed relationships and date validity - "what changed since last month?" It's not RAG. RAG re-derives answers from raw chunks every time. Here the LLM compiles knowledge into wiki pages once, keeps them current as new sources arrive, and the graph tracks how everything connects. Works with any MCP-compatible agent (Claude Code, OpenAI Codex, Cursor, Gemini CLI). https://github.com/AyanbekDos/memoriki
Does the same job
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- AKA Karpathy-style LLM wiki your agents maintain (Markdown and Git)Apr 2026 · github.com · ▲260
I shipped a wiki layer for AI agents that uses markdown + git as the source of truth, with a bleve (BM25) + SQLite index on top. No vector or graph db yet. It runs locally in ~/.wuphf/wiki/ and you can git clone it out if you want to take your knowledge with you. The shape is the one Karpathy has been circling for a while: an LLM-native knowledge substrate that agents both read from and write into, so context compounds across sessions rather than getting re-pasted every morning. Most implementations of that idea land on Postgres, pgvector, Neo4j, Kafka, and a dashboard. I…
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