llmwiki is a free, open source documentation & knowledge base project written in Python and released under Apache-2.0. It has 1,746 GitHub stars, 245 forks and 28 open issues, and was last pushed 2 days ago. On this registry it ranks #66 of 100 tracked projects in Documentation & Knowledge Base, with 5 head-to-head comparisons available. It gained 89 stars over the last 30 tracked days.

What is llmwiki?

LLM Wiki is an open-source, Apache-2.0 Python project that turns a folder of documents, notes, and web clippings into an autonomous, self-maintaining personal Wikipedia written and updated by Claude over MCP, built for individual readers, their AI assistants, and organizations that want a knowledge base they do not have to remember to update.

What it is

LLM Wiki is an implementation of Andrej Karpathy's LLM Wiki concept, with what the README describes as an increased emphasis on autonomous maintenance. The user captures documents, notes, and web clippings as they work, and a nightly Claude Routine synthesizes those sources into a permanent knowledge base. Because the clipper records highlights and margin notes alongside the source, the wiki becomes a record of not just what was read but what was thought about it, and it compounds over months and years. The project is designed to work at three distinct scales: for an individual, as a personal Wikipedia of what they have read; for an AI, as a context layer that lets an LLM apply the user's own mental models; and for an organization, as a self-maintaining institutional knowledge layer.

The concrete problem is scattered reading and research that never consolidates. Notes accumulate in folders, clippings pile up in browsers, and know-how generally lives in people's heads rather than in any durable artifact, because a hand-curated wiki depends on a person remembering to maintain it. LLM Wiki lives in the Python and Model Context Protocol ecosystem: the repository ships a Python API, an MCP server, and a Next.js web application, and it connects to MCP-compatible clients such as Claude.ai, Claude Cowork, Claude Code, and Codex. The specific thing it replaces is the manually maintained personal wiki or second-brain, where the user is the only editor and the only indexer.

Key capabilities

  • An MCP server that connects Claude.ai, Claude Cowork, Claude Code, Codex, or any other MCP-compatible application to the wiki.
  • A Chrome extension that clips webpages and PDFs as the user reads, capturing highlights and comments that Claude can see over MCP.
  • Upload support for Markdown, PowerPoint, PDFs, Word documents, and more, with optional LibreOffice extraction for Word and PowerPoint files and an optional MISTRAL_API_KEY for higher-quality PDF OCR.
  • A Next.js web app for navigating the generated Wikipedia and viewing the underlying sources behind any page.
  • Native cross-linking between wiki pages and back to the sources those pages came from.
  • A graph viewer that shows how concepts and entities relate to one another.
  • Visualizations, including charts, SVGs, and Mermaid diagrams.
  • A CLI entry point, ./llmwiki open ~/research, which initializes the workspace, indexes the folder into a local search index, starts the API and web app, and opens localhost:3000.

Who uses it and how

  • Individual researchers and readers point the CLI at an existing folder of material, such as ~/research, and let a nightly Claude Routine synthesize new sources into wiki pages without manual filing.
  • Users of Claude or other MCP clients connect the MCP server so that their own accumulated mental models become a context layer the model can apply when working with them.
  • Organizations adopt the pattern to address poor institutional memory, where know-how lives in people's heads rather than in a maintained knowledge layer.
  • Teams wanting a zero-install path can try the hosted option at llmwiki.app, or self-host the remote app for a more shared deployment.
  • Local mode is intentionally loopback-only: the API listens on 127.0.0.1 and does not support LAN or remote binding, so single-machine use is the default posture.

Getting started

LLM Wiki supports remote and local modes: either self-host the remote app, try it free at llmwiki.app, or clone the repository and use the CLI. For local use, requirements are Python 3.11+ and Node.js 20+, followed by git clone https://github.com/lucasastorian/llmwiki.git, pip install -r api/requirements.txt -r mcp/requirements.txt, and npm install inside web/, then ./llmwiki open ~/research on macOS and Linux or python llmwiki open C:\Users\you\research on Windows.

How it compares

The facts supplied do not name any paid products that this project replaces, and they do not name any comparable open-source tools either. It stands alone in this registry in that respect, with Karpathy's LLM Wiki concept named only as the architectural inspiration rather than as a competing implementation.

When to use it — and when not to

A self-hoster must run Python 3.11+ and Node.js 20+, and should expect to install LibreOffice if Word and PowerPoint extraction matters or supply a MISTRAL_API_KEY if good PDF OCR matters. Because local mode binds only to 127.0.0.1, anyone needing LAN or remote access for a shared team deployment must self-host the remote app rather than use the local path. The project also assumes an ongoing Claude or MCP-compatible account, so users who cannot connect an MCP client, or who want a purely manual editor, are not the right audience; note also that the README excerpt available here is truncated, so details of the hosted mode and the index layout are only partly documented.

Sources: LLM Wiki, repository.

project readme (upstream, from github) — read inline

LLM Wiki

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

License

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
cd web && npm install && cd ..

Windows (PowerShell):

git clone https://github.com/lucasastorian/llmwiki.git
cd llmwiki
python -m venv .venv
.venv\Scripts\Activate.ps1
pip install -r api/requirements.txt -r mcp/requirements.txt
cd web; npm install; cd ..

If activation is blocked by your execution policy, run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or skip activation and use .venv\Scripts\python in place of python below.

2. Point it at a folder of your files — PDFs, Word documents, PowerPoints, Markdown, notes. Use any folder on your disk (it does not go inside this repo): the one that already holds your documents, or a fresh empty one. LLM Wiki indexes it into a local search index so the files show up in the app and Claude can read them. It never moves, modifies, or uploads your files — the only things it adds are a wiki/ folder for generated pages and a hidden .llmwiki/ index (see What happens on disk).

./llmwiki open ~/research                     # macOS / Linux
python llmwiki open C:\Users\you\research     # Windows

This initializes the workspace, indexes the folder, starts the API and web app, and opens localhost:3000. Local mode is intentionally loopback-only: the API listens on 127.0.0.1 and does not support LAN or remote binding.

To preview the hosted onboarding UX locally without authentication or API writes, start the web app with the development-only preview flag and open localhost:3000/onboarding:

cd web
NEXT_PUBLIC_ONBOARDING_PREVIEW=true npm run dev

Restart the development server after changing this flag. The preview simulates creation and completion in memory; it does not create a wiki or change onboarding state.

3. Connect Claude over MCP. MCP enables Claude to read, write, and search your wiki.

./llmwiki mcp-config ~/research                     # macOS / Linux
python llmwiki mcp-config C:\Users\you\research     # Windows

Paste the printed JSON into claude_desktop_config.json (Claude Desktop) or .claude/settings.json (Claude Code). One workspace is one MCP server entry, so add one per folder. Then tell Claude: "Read the guide, then ingest my sources and start building the wiki."

4. Make it self-maintaining. Set up a Claude Routine — a scheduled prompt that runs on its own — so Claude refreshes the wiki without you having to remember to. Each run, it reads whatever's new in the workspace since last time (uploads, notes, and clips and highlights from the Chrome extension) and updates the pages those sources touch. You curate the sources; the wiki keeps itself current.

A routine prompt that works well:

Read the guide. Find everything added to the workspace since your last run — new sources, clips, and highlights. For each one, read it and update the wiki: write new pages where they're warranted, fold new material into existing pages, and fix any cross-references or citations it affects.

Then schedule that prompt to run nightly. Claude Code Routines run it on Anthropic's cloud on a fixed cadence even when your laptop is closed — create one at claude.ai/code/routines, with /schedule in the CLI, or from Claude Cowork — while a Desktop scheduled task runs the same prompt on your own machine. Either way the wiki compounds: a year from now you can open it and read back the ideas you were working through a year ago.

Adding content

There are two ways to get material into your wiki.

Upload. Drag files into the web app, or just drop them into the workspace folder — the background watcher picks them up and indexes them. Markdown, PDF, Word, PowerPoint, Excel, images, and more. Each file becomes searchable and readable by Claude.

Chrome extension. Clip web pages and PDFs as you read, highlight the parts that matter, and leave comments. Everything you save lands in the same workspace, and your highlights and notes are visible to Claude over MCP — so a nightly routine can fold them into the wiki on its own.

Install from the Chrome Web Store →

The extension works in both modes. By default it talks to the hosted app; flip the toggle to Local and it points at your running workspace at http://localhost:8000 — so anything you clip while ./llmwiki open is running goes straight into your local wiki. Pick a destination folder (default /webclipper/) and start saving.

Supported files

Type Formats How it's handled
PDF .pdf Text and figures extracted locally. Set MISTRAL_API_KEY for higher-quality OCR on tables and complex layouts.
Office .docx .doc .pptx .ppt Converted with LibreOffice, then extracted — requires a local LibreOffice install.
Spreadsheets .xlsx .xls Extracted sheet by sheet.
Web pages .html .htm Cleaned to readable Markdown, stripping nav and ads.
Text & data .md .txt .csv .json .xml .yaml .svg, and more Indexed and chunked directly.
Images .png .jpg .webp .gif Stored and viewable inline; Claude can read them when asked.

What happens on disk

LLM Wiki adds exactly two things to the folder you point it at. Your source files are never moved, modified, or uploaded — they stay exactly where they are.

~/research/                  # your files, untouched
  papers/paper.pdf
  notes.md
  data.xlsx
  wiki/                      # generated pages — created by LLM Wiki
    overview.md
    concepts/
      attention.md
  .llmwiki/                  # index + cache — hidden, rebuildable
    index.db
    cache/
  • wiki/ holds ordinary Markdown files. Claude writes and updates them over MCP, but they're just files — open them in any editor, commit them to git, edit them by hand.
  • .llmwiki/ is a derived layer: a local SQLite search index (index.db) and extracted artifacts (cache/). It's safe to delete — ./llmwiki reindex ~/research rebuilds it from your source files.

The filesystem is the source of truth; the index just makes it fast to search. A background watcher notices changes you make outside the app and re-indexes them, so editing a wiki page in your own editor stays in sync.

What Claude can do

Once connected over MCP, Claude works the wiki through a small, deliberate set of tools — the same set in local and hosted mode:

Tool What it does
guide Orients Claude — how the vault works and which knowledge bases exist. It calls this first.
create_knowledge_base Creates a knowledge base and starter overview.md; local mode returns the existing singleton workspace.
list_knowledge_bases Lists your knowledge bases and their slugs (every other tool takes one).
search Browse files, full-text search across content, or query the citation graph — what cites what, plus stale or uncited pages.
read Read documents — a single file or a glob batch, PDF/office page ranges, optionally with embedded images.
create Create a wiki page, note, or asset (SVG diagram, CSV) with footnote citations back to sources.
edit Find-and-replace exact text in an existing page.
append Add content to the end of a page.
delete Remove pages or sources by path or glob (overview.md and any legacy log.md are protected).
lint Deterministic hygiene checks — citation resolution, dangling links, orphan and stale pages, frontmatter consistency.

Writes go to the source of truth first — a file on disk in local mode, Postgres in hosted mode — then the search index updates. So when Claude creates /wiki/concepts/attention.md, it's a real file (or row) immediately, not a pending change.

Architecture

Three kinds of client reach the workspace, through two entry services, over one storage abstraction:

  Claude  ──MCP──►  MCP server ─┐
                                │                local mode  →  SQLite + your filesystem
  Web app ──HTTP─►  API ────────┼──►  VaultFS  ─┤
                                │                hosted mode →  Postgres + S3
  Chrome  ──HTTP─►  API ────────┘
                      └──►  Converter  (PDF / Office text extraction)

VaultFS is the seam: the same wiki operations run against a SQLite-plus-filesystem backend locally or a Postgres-plus-S3 backend when hosted, so Claude's tools behave identically either way. The MCP server speaks to Claude; the API serves the web app and the Chrome extension; the converter handles heavier PDF and Office extraction. Whatever the backend, the durable store is the source of truth and the search index is derived from it.

What's next

Today you add content two ways: upload, or the Chrome extension. The wiki is only as good as what reaches it, so the roadmap is mostly about widening that funnel — more channels for capturing what you read, write, and discuss:

  • Slack — save messages and threads, and ask the wiki questions, without leaving Slack. This is the natural channel for the institutional-memory case: most of what an organization knows is already flowing through chat.
  • Granola — pull in your meeting notes automatically, so the conversations you have become part of your memory alongside the things you read.
  • Email / forward-to-save — a dedicated address you forward articles, newsletters, and notes to; they land in the workspace and the nightly routine folds them in.
  • Public ingest API + webhooks — a documented endpoint so scripts and other tools can push content into a workspace programmatically, plus a Zapier integration to wire up the apps you already use without writing code.

The throughline: capture should meet you wherever you already read and think, and the wiki keeps itself current from there.

License

Apache 2.0 — see LICENSE.

Frequently asked questions

Is llmwiki free to use?

llmwiki is open source under the Apache-2.0 licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does llmwiki do?

Open Source Implementation of Karpathy's LLM Wiki. Upload documents, connect your Claude account via MCP, and have it write your wiki !

What is llmwiki written in?

llmwiki is primarily written in Python. Its source is publicly available at https://github.com/lucasastorian/llmwiki, and it has 1,746 GitHub stars.