首次启动必须用 .env 里的 ATOMIC_SETUP_TOKEN 在向导中认领实例;需要先配置 OpenRouter、Ollama 或 OpenAI 兼容的 AI 提供方,否则嵌入、打标、Wiki 和聊天不可用;Docker Compose 默认经 nginx 代理暴露在 8080 端口,已有反向代理可跳过该服务。
git clone https://github.com/kenforthewin/atomic.git
cd atomic
echo "ATOMIC_SETUP_TOKEN=$(openssl rand -base64 24)" > .env
docker compose up -dREADME 未说明显存或 GPU 要求;桌面版支持 macOS、Linux、Windows,服务端可用 Docker 或 Fly.io 部署,也可用 cargo 直接运行。
自托管的个人知识库,把 Markdown 笔记自动切块、向量化并连成语义知识图谱
自托管的个人知识库,用语义关联把零散笔记自动串起来,适合想自己掌控数据、又需要智能检索的人。
核心能力
- 把笔记切成原子块并用 sqlite-vec 做向量语义检索
- 按语义相似度用力导向图在 Canvas 上布局知识
- 用 LLM 从笔记合成带行内引用的 Wiki 文章
- 提供 Agentic RAG 聊天,对话中实时检索知识库
- 内置 MCP 端点,供 Claude 等 AI 工具读写原子
容易踩的坑
- v1.45.0Atomic v1.45.0最新正式版2026-08-09 · 2026-08-09 20:33 UTC
v1.45.0 — 2026-08-09
- Fix auto-tagging, tag merges, and wiki updates silently producing empty results on certain AI providers by moving generative structured calls to prompt-level schema enforcement
- Fix gateway-padded 200 responses (common on OpenRouter) being classified as permanent failures instead of retryable errors, which caused auto-tagging to waste retry budget and drop atoms
- Improve structured output instructions with concrete examples derived from the schema, significantly improving reliability on smaller local models (e.g. llama3.2)
Download the assets below to install.
- v1.44.0Atomic v1.44.02026-08-08 · 2026-08-08 22:25 UTC
查看更新说明
v1.44.0 — 2026-08-08
- Add per-tag wiki prompt overrides — customize the generation and update instructions for any tag's wiki article via the tag context menu, wiki card actions, or the reader header
- Add quick-access ⋮ menus on wiki article cards and suggestion cards for prompt editing, regeneration, and deletion — also makes these actions reachable on touch devices for the first time
- Fix context menu item clicks incorrectly triggering the underlying card or row action (e.g. opening the reader on top of a just-opened modal)
Download the assets below to install.
- v1.43.0Atomic v1.43.02026-08-04 · 2026-08-04 01:36 UTC
查看更新说明
v1.43.0 — 2026-08-04
- Add a fully streaming chat experience with token-by-token rendering, stop/cancel, auto-titled conversations, boolean scope modes (include/require/exclude), knowledge-base tools (tags, wikis, reports), cited sources, save-answer-as-atom, and a fullscreen desktop mode
- Add a contextual left sidebar that adapts to the current view — table of contents with scrollspy in readers, article list in the wiki view, recent atoms on the dashboard, and latest findings on reports
- Expand the MCP server from 6 to 16 tools — adds tag browsing, wiki and report reading, semantic neighbors, database listing, and atom pagination — with per-client setup docs for Claude, Cursor, and ChatGPT
- (Cloud) Improve wiki update reliability by switching to section-level edits that preserve untouched content byte-for-byte, and fix multiple AI-provider truncation issues that could produce cut-off wiki articles and report digests
- Polish the top bar and chat UI — icon-only database switcher, centered send button, hover-revealed conversation actions, and report name as the dashboard heading instead of a generic greeting
- (Cloud) Fix global search failing on cloud, canvas clusters showing generic names instead of topic labels, and multiple memory-retention issues with WebSocket and MCP session cleanup
Download the assets below to install.
- v1.42.2Atomic v1.42.22026-07-13 · 2026-07-13 23:42 UTC
查看更新说明
v1.42.2 — 2026-07-13
- Fix embedding failures on atoms with very large code blocks (e.g. RSS-ingested posts with 60KB+ fenced code) by splitting oversized blocks at line boundaries
- Enable markdown export for Atomic Cloud users — the Export button is no longer hidden and works with tenant-scoped isolation
- Improve embedding speed by routing to the lowest-latency OpenRouter upstream, avoiding a pathological provider that could stall requests for 13–80 seconds
- Reduce canvas rebuild cost on Cloud by averaging chunk embeddings in SQL instead of transferring all vectors to the app server, and widen the rebuild debounce to avoid redundant recomputes during batch pipelines
- Fix Atomic Cloud checkout: Stripe webhook parsing now handles the current API shape, and post-checkout redirects land on the correct tenant URL instead of a 404
- Update curated Cloud model lists — Pro tier adds Claude Sonnet 5, GPT-5.6 Terra, and GLM-5.2; Free tier swaps to Gemini 3.1 Flash Lite
Download the assets below to install.
- v1.42.1Atomic v1.42.12026-07-11 · 2026-07-11 22:00 UTC
查看更新说明
v1.42.1 — 2026-07-11
- Fix text selection not being visible when drag-selecting inside code blocks in the editor
Download the assets below to install.
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
☁️ Atomic Cloud — Atomic, hosted at your own subdomain. Try it out for free. Everything below still self-hosts forever.
A personal knowledge base that turns markdown notes into a semantically-connected, AI-augmented knowledge graph.
Atomic stores knowledge as atoms — markdown notes that are automatically chunked, embedded, tagged, and linked by semantic similarity. Your atoms can be synthesized into wiki articles, explored on a spatial canvas, and queried through an agentic chat interface.
https://github.com/user-attachments/assets/1992fcf7-1d6b-41b1-a177-2da2e8b57676

Wiki synthesis — LLM-generated articles with inline citations

Canvas — view your knowledge on an interactive graph

Semantic search — find by meaning, not keywords

Features
- Atoms — Markdown notes with hierarchical tagging, source URLs, and automatic chunking
- Semantic Search — Vector search over your knowledge base using sqlite-vec
- Canvas — Force-directed spatial visualization where semantic similarity determines layout
- Wiki Synthesis — LLM-generated articles with inline citations, built from your notes
- Reports — Scheduled research tasks that turn your atoms into recurring cited findings (daily briefings, contradiction scans, open-question tracking)
- Chat — Agentic RAG interface that searches your knowledge base during conversation
- Auto-Tagging — LLM-powered tag extraction organized into hierarchical categories
- Multiple AI Providers — OpenRouter, Ollama, or any OpenAI-compatible provider for embeddings and LLMs
- RSS Feeds — Subscribe to feeds and automatically sync new articles as atoms
- Browser Extension — Capture web content directly into Atomic (Chrome Web Store)
- MCP Server — Expose your knowledge base to Claude and other AI tools
- Multi-Database — Multiple knowledge bases with a shared registry
- iOS App — Native SwiftUI client for reading and writing atoms on mobile (App Store)
Getting Started
Atomic runs as a desktop app (Tauri), a headless server (Docker/Fly.io), or both.
Desktop App
Download the latest release for your platform from GitHub Releases (macOS, Linux, Windows).
On first launch, the setup wizard walks you through AI provider configuration.
Self-Host with Docker Compose
git clone https://github.com/kenforthewin/atomic.git
cd atomic
echo "ATOMIC_SETUP_TOKEN=$(openssl rand -base64 24)" > .env
docker compose up -d
This starts three services: the API server, the web frontend, and an nginx reverse proxy. Open http://localhost:8080 and claim your instance through the setup wizard with the ATOMIC_SETUP_TOKEN value from .env.
The proxy service is provided for convenience — if you already run your own reverse proxy (Caddy, Traefik, etc.), you can skip it and route traffic to the server and web containers directly. See docker/nginx.conf for an example configuration.
Deploy to Fly.io
cp fly.toml.example fly.toml
fly launch --copy-config --no-deploy
fly volumes create atomic_data --region <your-region> --size 1
fly secrets set ATOMIC_SETUP_TOKEN="$(openssl rand -base64 24)"
fly deploy
Open https://your-app.fly.dev and claim your instance with the setup token. The public URL for OAuth/MCP is auto-detected from the Fly app name.
Standalone Server
ATOMIC_SETUP_TOKEN="$(openssl rand -base64 24)" \
cargo run -p atomic-server -- --data-dir ./data serve --port 8080
On first run, enter ATOMIC_SETUP_TOKEN in the setup wizard, or create an API token directly:
cargo run -p atomic-server -- --data-dir ./data token create --name default
AI Provider Setup
Atomic needs an AI provider for embeddings, tagging, wiki generation, and chat.
- OpenRouter — Get an API key from openrouter.ai. Supports separate model selection for embedding, tagging, wiki, and chat.
- Ollama — Install Ollama and pull models (e.g.,
ollama pull nomic-embed-text). Atomic auto-discovers available models. - OpenAI-compatible — Any provider with an OpenAI-compatible API (e.g., OpenAI, Azure OpenAI, Together, Groq). Configure the base URL and API key.
Configure via the setup wizard on first launch, or later in Settings.
Browser Extension
The Atomic Web Clipper captures web content as atoms. Install from the Chrome Web Store, then configure your server URL and API token in the extension options.
Captures are queued offline and synced when the server is available.
MCP Server
Atomic exposes an MCP endpoint for Claude and other AI tools to search, read, create, update, and ingest atoms.
Desktop App (Local Mode)
The desktop app bundles atomic-mcp-bridge, a stdio-to-HTTP bridge that reads the local auth token automatically. No token configuration needed — just point your MCP client at the binary:
{
"mcpServers": {
"atomic": {
"command": "/Applications/Atomic.app/Contents/MacOS/atomic-mcp-bridge"
}
}
}
The app's Settings > Integrations page shows the exact path for your system.
Remote / Self-Hosted
For remote servers or the web app, connect via the HTTP endpoint at /mcp with a Bearer token:
{
"mcpServers": {
"atomic": {
"type": "url",
"url": "https://your-server.com/mcp",
"headers": {
"Authorization": "Bearer YOUR_TOKEN"
}
}
}
}
Create a token from Settings > Connection > API Tokens, or via the CLI:
atomic-server token create --name "claude"
Available tools: search and retrieval (semantic_search, read_atom, find_similar), browsing (list_tags, list_atoms, list_databases), synthesized knowledge (list_wikis, get_wiki, list_reports, get_report_findings), writing (create_atom, ingest_url, update_atom, edit_atom), and ChatGPT-compatible search/fetch aliases. See the MCP Server guide for per-client setup (claude.ai, Claude Code, Cursor, ChatGPT).
Architecture
All business logic lives in atomic-core, a standalone Rust crate with no framework dependencies. atomic-server wraps it with a REST API, WebSocket events, and an embedded MCP endpoint. Every client connects to atomic-server over HTTP:
+------------------+
| atomic-core |
| (all logic) |
+--------+---------+
|
+--------v---------+
| atomic-server |
| (REST + WS + MCP)|
+--------+---------+
+---------+----+----+---------+
v v v v
+-----------+ +----------+ +------+ +----------+
| src-tauri | | React UI | | iOS | |mcp-bridge|
| (sidecar) | | (browser)| | app | | (stdio) |
+-----+-----+ +----------+ +------+ +-----+----+
| |
+-----v-----+ +-----v-----+
| React UI | | MCP clients|
| (desktop) | |(Claude,etc)|
+------------+ +------------+
Project Structure
Cargo.toml # Workspace root
crates/atomic-core/ # All business logic
crates/atomic-server/ # REST + WebSocket + MCP server
crates/mcp-bridge/ # HTTP-to-stdio MCP bridge
src-tauri/ # Tauri desktop app (launches server as sidecar)
src/ # React frontend (TypeScript)
extension/ # Chromium browser extension
scripts/ # Import and utility scripts
Development
Prerequisites
- Node.js 22+
- Rust toolchain (rustup)
- For the desktop app: platform-specific Tauri v2 dependencies
Commands
npm install # Install frontend dependencies
# Desktop app
npm run tauri dev # Dev with hot reload
npm run tauri build # Production build
# Server only
cargo run -p atomic-server -- serve --port 8080
# Frontend only
npm run dev # Vite dev server
# Checks
cargo check # All workspace crates
cargo test # All tests
npx tsc --noEmit # Frontend type check
Tech Stack
| Layer | Technology |
|---|---|
| Core | Rust, SQLite + sqlite-vec, tokio |
| Desktop | Tauri v2 |
| Server | actix-web |
| Frontend | React 18, TypeScript, Vite 6, Tailwind CSS v4, Zustand 5 |
| Editor | CodeMirror 6 |
| Canvas | Sigma.js, Graphology |
| AI | OpenRouter, Ollama, or OpenAI-compatible (pluggable) |
License
MIT