Agent Skills-compatible LLM wiki for Claude Code, Cursor, and Codex. Build a Karpathy-style knowledge base from raw sources, citations, and linting.
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.
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.
A cyber brain for your AI. It never forgets a detail, remembers exactly what you said, and learns how you work over time. Free, local, works with Cursor, Claude Code, Codex, OpenClaw, Hermes and more. 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 skill & 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.
Your markdown vault, compiled into a 6-persona MCP team for Claude Code, Codex, OpenCode, and Gemini CLI. Headless-first. Cites, doesn't guess.
Compile documents into a living Obsidian wiki. Any AI agent. Based on Karpathy's LLM Wiki pattern.
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.
Repository-scoped memory for coding agent's decisions, pitfalls, and handoffs stored in one inspectable SQLite file, so agents continue instead of starting over.
Give your AI a memory. Drop-in learning layer for any LLM — no retraining, no RAG setup.
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.
Give every AI agent persistent memory of your team's knowledge. No vector DB, no RAG — just Git + BM25 + 114 tokens per session.
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.
Memory that forgets: a persistent, self-revising belief-state MCP server for agentic R&D. Uses a hypothesis DAG to auto-prune dead ends and deduce truth without extra probes.
The Karpathy LLM Wiki, production-ready. Zero-RAG personal knowledge base with MCP server, multi-agent support, knowledge graph visualization, and hallucination enforcement. No embeddings, no vector DBs — just markdown + git.
Open protocol for traversable knowledge networks. CBB traversal lets an 8B model match frontier AI on domain-specific queries.
Add a description, image, and links to the rag-alternative topic page so that developers can more easily learn about it.
To associate your repository with the rag-alternative topic, visit your repo's landing page and select "manage topics."