一个由人工智能构建和维护的自主、自我维护的个人维基百科。

LLM Wiki 将你零散的阅读和研究转化为一个持续存在、由 AI 维护的第二大脑。在工作过程中捕捉文档、笔记和网页剪报，并部署每晚的 Claude 程序，自主地将这些来源整合成永久的知识库。由于 clipper 会在资料旁边记录你的重点和边注，wiki 不仅记录你读了什么，还记录了你对它的想法——这种记录会在原有语境消失后，持续数月甚至数年积累。这种架构深受 Andrej Karpathy 的 LLM Wiki 概念启发，更加强调自主维护。

LLM Wiki 设计用于三个不同的规模：

• 给你 — 你读过的个人维基百科，不必记得更新。
• 用于你的AI — 为大型语言模型提供上下文层，帮助它们在与你合作时应用自己的心理模型。
• 对于你的组织 — 大多数组织的机构记忆较差，因为知识通常存在于人们的脑海中。

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