AI가 구축하고 유지하는 자율적이고 자율적인 개인 위키피디아.

LLM 위키는 흩어진 읽기와 연구를 AI가 유지하는 두 번째 뇌로 변환시킵니다. 작업 중에 문서, 노트, 웹 스크랩을 캡처하고, 매일 밤 Claude 루틴을 실행해 그 출처들을 자율적으로 종합하여 영구적인 지식 베이스로 만듭니다. 클리퍼가 출처와 함께 하이라이트와 여백 메모를 기록하기 때문에, 위키는 단순히 읽은 내용뿐만 아니라 그에 대해 생각한 것의 기록이 되며, 이는 원래 맥락이 사라진 후에도 수개월, 수년에 걸쳐 쌓여갑니다. 이 아키텍처는 Andrej Karpathy의 LLM 위키 개념에서 크게 영감을 받았으며, 자율적 유지보수에 더 중점을 두고 있습니다.

LLM 위키는 세 가지 뚜렷한 규모에서 작동하도록 설계되었습니다:

• 당신을 위해 — 읽은 내용을 개인적으로 정리한 위키피디아로, 굳이 업데이트하지 않아도 됩니다.
• 당신의 AI를 위해 — LLM이 당신과 작업할 때 자신의 정신 모델을 적용할 수 있는 맥락 레이어입니다.
• 귀하의 조직을 위해 — 대부분의 조직은 조직 기억이 부족합니다. 왜냐하면 노하우는 일반적으로 사람들의 머릿속에 있기 때문입니다.

LLM Wiki

An autonomous, self-maintaining personal Wikipedia built and maintained by AI.

LLM Wiki transforms your scattered reading and research into a persistent, AI-maintained second brain. Capture documents, notes, and web clippings as you work, and deploy a nightly Claude Routine to autonomously synthesize those sources into a permanent knowledge base. Because the clipper captures your highlights and margin notes alongside the source, the wiki becomes a record of not just what you read but what you thought about it — one that compounds over months and years, long after the original context would have faded. This architecture is heavily inspired by Andrej Karpathy’s LLM Wiki concept, with an increased emphasis on autonomous maintenance.

LLM Wiki is designed to work at three distinct scales:

• For you — a personal Wikipedia of what you’ve read that you don’t have to remember to update.
• For your AI — a context layer for LLMs to apply your own mental models when working with you.
• For your organization — most organizations have poor institutional memory, because know-how generally lives in people’s heads. We hope companies will consider adopting this model to build a self-maintaining institutional knowledge layer.

Features

• Connect via MCP Connect Claude.ai, Claude Cowork, Claude Code, or Codex (or any other MCP-compatible app)
• A Chrome extension Clip webpages and PDFs as you read, highlight key sections, and leave comments that Claude can see over MCP.
• Uploads Markdown, PowerPoint, PDFs, Word documents, and more.
• A clean Next.js web app to navigate your own wikipedia — and view the underlying sources.
• Native cross-linking between wiki pages, and back to the sources they came from.
• A graph viewer to see how your concepts and entities relate.
• Visualizations — Charts and other visualizations, including SVGs and Mermaid diagrams.

Getting started

LLM Wiki supports two modes: remote & local. You can self-host the remote app, or try it out for free at llmwiki.app. Or you can git clone the repository, and use the CLI to get started.

Here’s how to get started locally.

Requirements: Python 3.11+, Node.js 20+. Optional: LibreOffice to extract Word/PowerPoint files, and a MISTRAL_API_KEY for higher-quality PDF OCR.

1. Install. Clone the repo and install the Python and web dependencies.

macOS / Linux:

git clone https://github.com/lucasastorian/llmwiki.git
cd llmwiki
python -m venv .venv && source .venv/bin/activate
pip install -r api/requirements.txt -r mcp/requirements.txt