Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Read-only access to your Molio local knowledge base: search, read, browse, and AI Q&A.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
MOLIO_PORT필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"molio": {
"command": "npx",
"args": [
"-y",
"@molio/cli",
"mcp"
],
"env": {
"MOLIO_PORT": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add molio --env MOLIO_PORT=your-value -- npx -y @molio/cli mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"molio": {
"command": "npx",
"args": [
"-y",
"@molio/cli",
"mcp"
],
"env": {
"MOLIO_PORT": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"molio": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@molio/cli",
"mcp"
],
"env": {
"MOLIO_PORT": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
MOLIO_PORT env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 zhuzhaoyun 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.2)은 13일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Give AI your personal knowledge base. Local-first, and every byte stays yours.
English · 中文 · 🌐 Official Website
What you've accumulated isn't one kind of thing: experience and methods scattered across notes, documents, and chat logs — and also whole books, PDFs full of figures, piles of industry material. Most of it sits in a form AI can't read, so every conversation starts from zero.
Molio turns all of it into a personal knowledge base that AI can read and use: Claude Code, Codex, and other agents enter your knowledge space, work on top of everything you've accumulated — researching, writing, answering, analyzing — and write their results back as Markdown, so the base grows thicker with every task. Everything runs on your machine, never through a third-party server.
Starting from zero? The resource library ships ready-made knowledge bases that keep growing — import one and start asking.
▶ Click to watch the demo — one book, one knowledge universe: 1,362 years of history from the *Zizhi Tongjian*, processed by Molio into an AI-explorable knowledge base
01 · Collect & Process — scattered fragments, or a whole book, all become a callable knowledge base
Input isn't limited by format: clip pages with one click via the Web Clipper, open your Obsidian vault directly, or batch-import local documents. Scanned PDFs and Word / PPT / Excel files go through the bundled docling for layout analysis, OCR, and table reconstruction; images are read by OCR; million-word books run through a chunked preprocessing and digest pipeline with resumable progress. What lands on disk is plain Markdown — zero migration, no lock-in.
The Wiki engine then extracts entities and concepts from that unified Markdown layer, weaving dense cross-links and layered indexes — data becomes a foundation only after it's processed.
02 · Work & Task — agents run on your data
Claude Code, Codex, Gemini CLI, Qwen Code — agents work inside your knowledge space, researching, writing, answering, and analyzing. What they see is no blank slate, but everything you've accumulated. Pick an agent in a unified GUI with streaming output; scan a QR code to chat with your base from your phone via WeChat.
03 · Reflow & Deposit — the base grows thicker with use
Every task's output is written back as Markdown — a reusable, long-term asset. The knowledge graph keeps growing, so the next task starts from higher ground. Ready to publish? Typeset with doocs/md and distribute to 30+ platforms in one click.
| Input | What happens |
|---|---|
| Markdown / TXT / HTML / CSV and other text | Read as-is — the default shape of a knowledge base |
| Layout analysis + OCR + table reconstruction → Markdown | |
| Word / PPT / Excel | Same pipeline, heading hierarchy and tables preserved |
| Images (PNG / JPG / TIFF) | OCR text extraction |
| Web pages | One-click clip, or article extraction for WeChat posts |
| Obsidian vault | Opened in place — original files are read-only |
| Million-word books | Chunked preprocessing + digest pipeline, resumable |
PDF and Office conversion is handled by the bundled docling skill. The first conversion downloads the tool plus ~500MB of models; later runs reuse the cache.
Beyond the tool itself, Molio offers ready-made structured knowledge graphs — entire books and professional domains pre-organized into AI-ready knowledge bases you can import in one click, no building from scratch.
Covering literature, history, philosophy, traditional Chinese medicine, medicine, and AI engineering, with new resources added regularly. Highlights include the ontology knowledge base, the *Zizhi Tongjian* knowledge system, and an obstetric-ultrasound knowledge base. See the resource library for the full, always-current catalog.
These are uniquely structured assets that AI cannot conjure on its own. Import one into Molio and instantly run AI Q&A, relationship lookup, and topical research.
[Browse all resources →](https://molio.cn/resources.html)
A single Molio instance can serve multiple channels in parallel. Most channels can be onboarded right from the Web console.
| Channel | Text | Image | File | Voice | Group |
|---|---|---|---|---|---|
| Web Console *(default)* | ✅ | ✅ | ✅ | ✅ | — |
| ✅ | ✅ | ✅ | ⏳ | ⏳ | |
| Feishu | ✅ | ✅ | ✅ | ⏳ | ✅ |
| Telegram | ⏳ | ⏳ | ⏳ | ⏳ | ⏳ |
| Slack | ⏳ | ⏳ | ⏳ | — | ⏳ |
| Discord | ⏳ | ⏳ | ⏳ | — | ⏳ |
✅ Supported · ⏳ Planned · — N/A
Agent Workbench: multi-agent support with streaming responses
Knowledge Space: vault file tree with Markdown rendering
Knowledge Graph: visual map of your knowledge connections
Publishing: one-click sync to 30+ platforms
Download the latest release from GitHub Releases:
Molio-Setup-x.x.x.exeMolio-x.x.x.dmgInstall and launch. On first run, you'll be guided to configure an AI runtime CLI (e.g., Claude Code, Codex, Gemini).
Run Molio as a self-hosted web service on a NAS or server. A single container bundles the daemon, web UI, and Claude Code CLI, and works on both linux/amd64 and linux/arm64 — Synology, QNAP, TerraMaster, TrueNAS, Unraid, and most other NAS devices.
⚠️ How this differs from the desktop app (read before deploying)
- Browser access only — there is no desktop client for this mode. The Electron desktop app only ever talks to the daemon it launches locally (
localhost); it cannot connect to a container running on a remote NAS/server.
- The daemon runs inside the container and can only read/write directories mounted into it. The desktop workflow of "pick any local folder as a knowledge base via a folder picker" does not apply here — the browser has no folder picker, so when you add a knowledge base you type a container-internal path (e.g.
/vaults/your-folder, not the NAS host path).
- To expose folders as knowledge bases, mount them under
/vaultsindocker-compose.ymlvolumes. Your data still stays entirely yours (on your NAS) — only the access model changes, from "desktop app" to "browser + mounted volumes".
One-click install (requires Docker + Docker Compose v2):
# China (recommended)
curl -fsSL https://molio-releases.oss-cn-guangzhou.aliyuncs.com/script/install.sh | bash
curl -fsSL https://raw.githubusercontent.com/zhuzhaoyun/Molio/main/install.sh | bash
bash install.sh
The script asks for your knowledge-base directory and port, then pulls the image and starts the service. When it finishes, open http:// :3100, then go to Settings → Runtimes to configure your AI model and API key. On first boot Molio auto-creates a default knowledge base on the mounted directory, so you land straight inside — no manual setup.
Manual install (if you prefer plain docker compose):
git clone https://github.com/zhuzhaoyun/Molio.git && cd Molio
cp .env.example .env # AI model is configured later in the web UI docker compose up -d # then open http:// :3100
Everyday commands (run inside the install directory, default ~/molio):
docker compose logs -f # follow logs
docker compose restart # restart docker compose pull && docker compose up -d # update to the latest image docke
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요