Agent Skills-compatible LLM wiki for Claude Code, Cursor, and Codex. Build a Karpathy-style knowledge base from raw sources, citations, and linting.
Karpathy’s LLM Wiki, 100% local with Ollama. Drop Markdown notes → AI extracts concepts → your Obsidian wiki auto-links and grows. Zero sharing. Your notes stay yours.
Synthadoc: An open-source LLM knowledge compilation engine that turns raw documents into structured, local-first wikis. A transparent, human-readable alternative to traditional RAG, which can be self-managed and self-improved without the use of any tools.
MCP memory server for AI coding assistants. Works with Claude Code, Cursor, Codex, Gemini CLI, Cline, Continue, Cherry Studio, Zed, Hermes, OpenClaw, and any MCP client. Local, encrypted, verbatim recall. MIT.
More than just Karpathy’s LLM Wiki, 100% local with Ollama. Drop Markdown notes → AI extracts concepts → your Obsidian wiki auto-links and grows. Zero sharing. Your notes stay yours.
Memoriki - LLM Wiki + MemPalace. Personal knowledge base with real memory.
Andrej Karpathy's LLM Wiki pattern as a Claude Code plugin — turn accumulated sources into a self-maintaining, scalable markdown knowledge base.
KnoLo Core is a local-first knowledge base engine built for small language models (LLMs). It packages your documents into a compact .knolo file and enables fully deterministic querying — no embeddings, no vector databases, no cloud services required. Designed for on-device and edge LLM deployments.
Compile documents into a living Obsidian wiki. Any AI agent. Based on Karpathy's LLM Wiki pattern.
Your markdown vault, compiled into a 6-persona MCP team for Claude Code, Codex, OpenCode, and Gemini CLI. Headless-first. Cites, doesn't guess.
A minimal CLAUDE.md template that turns any LLM CLI into a personal knowledge base. Drop in one file, start ingesting articles. Karpathy's LLM Wiki pattern.
Give every AI agent persistent memory of your team's knowledge. No vector DB, no RAG — just Git + BM25 + 114 tokens per session.
Muscle memory for Claude, OpenClaw, and AI agents. Zero-cost Hebbian memory system — learns which files matter through co-access patterns, predicts what you need next.
Synapse Context Engine (SCE) is a brain-inspired hypergraph-based AI memory architecture for persistent context, coherent reasoning, and long-term memory, designed for transparency and safety.
Give your AI a memory. Drop-in learning layer for any LLM — no retraining, no RAG setup.
A human–AI collaboration framework that works with LLM nature, not around it — natural language and purpose make RAG and agent orchestration unnecessary. Home of the Pang Principle.
Self-organizing retrieval fabric for AI memory — deployable MCP server, REST API, and Python SDK
Temporal Layered Context Memory (TLCM). The architecture for AI that treats memory as a living timeline instead of a flat filing cabinet.
The Karpathy LLM Wiki, production-ready. Zero-RAG personal knowledge base with MCP server, multi-agent support, and hallucination enforcement. No embeddings, no vector DBs — just markdown + git.
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