AI 클라이언트가 연결된 Markdown 위키를 검색, 읽기 및 확장할 수 있도록 하며, 수집된 문서에서 인용된 답변을 제공합니다.
다른 이름 openapi/gknowledge, gknowledge-mcp
- 스타
- 29
- Tools
- —
- 다운로드, 30일
- —
- 최신 버전
- 0.3.0
- 마지막 커밋
- 2026년 10월 27일
- 라이선스
- MIT
gknowledge MCP란?
gknowledge은(는) MCP server입니다. AI 클라이언트가 연결된 Markdown 위키를 검색, 읽기 및 확장할 수 있도록 하며, 수집된 문서에서 인용된 답변을 제공합니다.
프로젝트 README에서 생성된 요약
gknowledge MCP server 정보
gknowledge는 연구자와 개발자가 자신의 문서로부터 지속적으로 성장하는 지식 베이스를 구축할 수 있도록 지원합니다. 소스 파일을 수집하여 AI가 지속적으로 관리할 수 있는 연결된 Markdown 위키를 생성하는 LLM Wiki 패턴을 구현합니다. 이 시스템은 2단계 추출 프로세스를 사용하여 생성된 모든 페이지에 출처와 인용이 포함되도록 보장하며, 이를 통해 정보의 검토와 신뢰성을 높입니다.
사용자는 내장된 휴리스틱 엔진을 사용하여 시스템을 완전히 오프라인으로 실행하거나, Ollama, LM Studio, vLLM 또는 Sign in with ChatGPT를 통해 ChatGPT 플랜과 같은 선호하는 모델에 연결할 수 있습니다. 로컬 우선 프라이버시를 위해 설계되었으며, 모든 데이터를 YAML frontmatter가 포함된 일반 Markdown과 SQLite 인덱스로 저장하므로 Obsidian과 호환됩니다. MCP server를 통해 Claude Code, Codex 또는 Cursor와 같은 에이전트가 지식 베이스와 직접 상호작용할 수 있습니다.
gknowledge-mcp 명령을 통해 AI 클라이언트는 키워드 검색, 백링크를 포함한 페이지 읽기, 유형별 페이지 목록 표시, 인용된 답변을 제공하는 질문하기 등의 특정 작업을 수행할 수 있습니다. 또한 서버를 사용하여 수집을 위한 새로운 소스를 추가하거나 위키 내의 최근 활동을 모니터링할 수도 있습니다.
활용 사례
- 1자동 위키 확장AI 에이전트가 새로운 연구 논문을 수집하여 기존 Markdown 지식 베이스를 자동으로 업데이트하고 확장할 수 있습니다.
- 2에이전트 기반 위키 관리개발자가 코딩 어시스턴트를 로컬 지식 저장소에 연결하여 특정 위키 페이지를 검색하고 읽을 수 있습니다.
프로젝트의 README를 바탕으로 작성되었습니다. 모든 활용 사례는 해당 내용의 인용문과 대조하여 확인합니다.
gknowledge MCP 설치 방법
형식 확인: 2026년 11월 10일Claude Code에 gknowledge MCP 설치
$ claude mcp add gknowledge -- uvx gknowledge-mcpCursor에 gknowledge MCP 설치
~/.cursor/mcp.json
{
"mcpServers": {
"gknowledge": {
"command": "uvx",
"args": [
"gknowledge-mcp"
]
}
}
}VS Code에 gknowledge MCP 설치
.vscode/mcp.json
{
"servers": {
"gknowledge": {
"type": "stdio",
"command": "uvx",
"args": [
"gknowledge-mcp"
]
}
}
}Claude Desktop에 gknowledge MCP 설치
claude_desktop_config.json
{
"mcpServers": {
"gknowledge": {
"command": "uvx",
"args": [
"gknowledge-mcp"
]
}
}
}Codex에 gknowledge MCP 설치
~/.codex/config.toml
[mcp_servers.gknowledge] command = "uvx" args = ["gknowledge-mcp"]
Gemini CLI에 gknowledge MCP 설치
~/.gemini/settings.json
{
"mcpServers": {
"gknowledge": {
"command": "uvx",
"args": [
"gknowledge-mcp"
]
}
}
}자동 검사
2026년 11월 13일에 실행됨전체 보고서 →자동 검사를 통과했습니다. 이는 보안 감사가 아닙니다. 코드를 직접 읽고 서버에 필요한 최소한의 권한만 부여하십시오. 검사 방식
- 소스 저장소 연결 및 접근 가능통과
- 오픈 소스 라이선스 (OSI)통과
- 최근 1년 내 커밋 또는 릴리스통과
- 패키지 이름이 인기 패키지와 유사하지 않음통과
- 원격 엔드포인트가 HTTPS 사용검사되지 않음
- 파괴적인 도구에 라벨 표시됨검사되지 않음
- 모델에 대한 숨겨진 지침 없음통과
- 패키지와 의존성에 심각한 보안 권고 없음통과
README
GitHub에서 보기Install
One line, on Ubuntu 24.04+ and Debian 13+. It adds the signed gknowledge APT repository, so updates arrive with apt upgrade (other distributions get a per-user install):
curl -fsSL https://github.com/openapi/gknowledge/releases/latest/download/install.sh | bash
Or add the APT repository yourself. apt also pulls GTK 4, Libadwaita and PyGObject:
sudo curl -fsSLo /usr/share/keyrings/gknowledge.gpg https://openapi.github.io/gknowledge/gknowledge.gpg
sudo curl -fsSLo /etc/apt/sources.list.d/gknowledge.sources https://openapi.github.io/gknowledge/gknowledge.sources
sudo apt update && sudo apt install gknowledge
On any distribution, with Flatpak (the GNOME runtime comes from Flathub):
flatpak install --user https://openapi.github.io/gknowledge/io.github.openapi.Gknowledge.flatpakref
Both repositories are described at openapi.github.io/gknowledge.
Then open gknowledge from the app grid. To remove it: sudo apt remove gknowledge (or flatpak uninstall io.github.openapi.Gknowledge).
- Fedora, Arch and others: install PyGObject, GTK 4 and Libadwaita with your package manager, then run the one-line installer above. It installs into
~/.localwithout root. - From source:
git clone https://github.com/openapi/gknowledge && cd gknowledge && make install. - Single files: every version's
.deband Flatpak bundle is on the Releases page, e.g.sudo apt install ./gknowledge_all.debafter downloading gknowledge_all.deb.
Why gknowledge
If you have used LLM Wiki, Tolaria, OpenKnowledge, Reor or Khoj, you already know the loop: ingest sources, let the model build and maintain a wiki, then ask questions against it. gknowledge does the same thing as a real GNOME application.
- Native, not a web view. GTK 4 and Libadwaita, built to follow the GNOME HIG. No Electron, no Tauri, no browser engine.
- Works with no account. A built-in heuristic engine ingests and answers offline. Add a model when you want better synthesis.
- Your data stays yours. Markdown with YAML frontmatter plus a readable SQLite index. Open the folder in Obsidian or any editor.
- Cited, reviewable, incremental. Every generated page records its sources, answers cite pages, and a review queue keeps you in control.
The workflow you already know
| You know this from… | What it is | In gknowledge |
|---|---|---|
| Karpathy's LLM Wiki, LLM Wiki | Ingest: read a new source, update the pages it touches | Done: two-step extraction with provenance |
| Reor, Khoj | Ask: questions answered from your notes, with citations | Done: lexical search plus graph expansion, citations, saved answers |
| LLM Wiki, OpenKnowledge | index.md and log.md, [[wikilinks]], Obsidian-compatible vault |
Done |
| LLM Wiki, Tolaria | Review AI changes before they stick | Review queue done, Git diff planned |
| Karpathy's LLM Wiki, OpenKnowledge | Lint: orphans, contradictions, stale pages | Planned |
| LLM Wiki | Knowledge graph, clusters, gaps | Planned |
| Tolaria, OpenKnowledge, LLM Wiki | MCP server so agents can read and write the wiki | Done: gknowledge-mcp |
| LLM Wiki | Web clipper, folder watch, deep research | Planned |
See ROADMAP.md for dates and TODO.md for the backlog.
Karpathy's LLM Wiki, native on GNOME
In April 2026 Andrej Karpathy described the LLM Wiki pattern: instead of re-reading raw documents on every question, an LLM builds and maintains a persistent wiki that compounds over time. gknowledge implements it as a desktop app.
What we kept
- Three layers: immutable
sources/, the generatedknowledge/wiki, and settings that tell the engine how to work. - The operations: ingest (read a source, update the pages it touches) and query (answer from the wiki, with citations). Lint is next.
index.mdas the catalogue andlog.mdas the append-only history.- Plain Markdown with
[[wikilinks]]and YAML frontmatter, so the folder opens in Obsidian. - The human curates, the model maintains.
What we changed and added
- A native app instead of an idea file. GTK 4 and Libadwaita, with sources, wiki, assistant and review in one window.
- Works with no model at all. An offline engine ingests and answers; a model makes it better.
- Bring your own brain. Your ChatGPT plan through Sign in with ChatGPT, Ollama, or any OpenAI-compatible endpoint.
- Two-step ingest with provenance. Analysis first, then pages; every page records its sources.
- No empty pages, no duplicates. Pages are created only with real content, names are merged across sources ("Kasparov" and "Garry Kasparov"), minor names stay as mentions until a second source cites them.
- A review queue for what the model is unsure about.
- An MCP server, so Claude Code, Codex or Cursor can search, read and grow the same wiki.
Use your wiki from Claude Code, Codex or Cursor
gknowledge ships an MCP server. Point any agent at a project folder:
claude mcp add gknowledge -- gknowledge-mcp ~/Knowledge/my-project # Claude Code
codex mcp add gknowledge -- gknowledge-mcp ~/Knowledge/my-project # Codex CLI
For Cursor or other clients, add this to the MCP configuration:
{ "mcpServers": { "gknowledge": { "command": "gknowledge-mcp", "args": ["/home/you/Knowledge/my-project"] } } }
| Tool | What the agent can do |
|---|---|
search_wiki |
find pages by keyword |
read_page |
read a page with its sources and backlinks |
list_pages |
list pages by type |
ask |
get a cited answer, optionally saved back into the wiki |
add_source |
import and ingest a file |
recent_activity |
see what changed recently |
Try it from source
sudo apt install python3-gi gir1.2-gtk-4.0 gir1.2-adw-1 # Ubuntu / Debian
git clone https://github.com/openapi/gknowledge && cd gknowledge
make start # opens a demo project with six AI papers already ingested
make start also restarts the app whenever you edit the source, which makes it the fastest way to hack on gknowledge. Install it for daily use with make install.
Bring your own brain
| Provider | Needs | Notes |
|---|---|---|
| Offline (default) | nothing | Heuristic extraction and extractive answers. Fully private. |
| ChatGPT plan | A Plus or Pro account | Preferences, Provider, Sign in with ChatGPT. Usage is charged to your own plan, no API key. |
| Ollama / LM Studio / vLLM | A local server | Any OpenAI-compatible endpoint on your machine. |
| OpenAI-compatible cloud | An API key | OpenAI, OpenRouter, Together, and similar. |
Nothing is sent anywhere unless you pick a provider that is not offline.
How it compares
| gknowledge | LLM Wiki | Tolaria | OpenKnowledge | Reor (archived) | Khoj | |
|---|---|---|---|---|---|---|
| Native GNOME / GTK 4 | yes | Tauri | Tauri | Electron | Electron | web + Electron |
| Works offline, no key | yes | needs a model | AI optional | agent-driven | local model | self-host |
| Plain Markdown vault | yes | yes | yes | yes | yes | reads yours |
| Linux packaging | .deb, Flatpak |
.deb, AppImage |
AppImage, .deb |
.deb, .rpm |
AppImage | pip, Docker |
| License | MIT | GPL-3.0 | AGPL-3.0 | GPL-3.0 | AGPL-3.0 | AGPL-3.0 |
Details and history of each project are in DISTRIBUTING.md.
gknowledge is an alternative to…
gknowledge sits at the intersection of LLM-powered knowledge bases, local-first note tools, and document RAG systems. If you have used any of the tools below, you already understand the shape of the problem — gknowledge addresses it as a native GNOME/GTK application that is local-first, provider-agnostic, and usable fully offline (no API key required, thanks to a built-in heuristic extraction engine).
LLM wiki / auto-knowledge-base builders (the closest peers, several studied in NOTES.md):
- LLM Wiki (
nashsu/llm_wiki) — Tauri desktop app implementing Karpathy's incremental "LLM builds and maintains a wiki" pattern - Tolaria — files-first, git-first Markdown knowledge base with AI-assisted editing
- WeKnora (Tencent) — enterprise RAG + agents + auto-wiki framework
- OpenKnowledge (Inkeep) — WYSIWYG Markdown editor with agent/MCP integrations for LLM wikis
- Reor — local-first AI note-taking that auto-links related notes
- Khoj — self-hostable AI "second brain" over your documents
Not a peer: Google NotebookLM offers a similar cited-notebook experience but is closed-source and cloud-only.
Document RAG / "chat with your knowledge" engines:
Local-first / networked-thought note tools (which gknowledge complements with automated ingestion and provenance):
- Obsidian (+ Smart Connections / Copilot plugins), Logseq, SiYuan, Trilium Notes, Zettlr, Foam, Dendron, Joplin, Notion, Tana, Capacities, Heptabase, RemNote
Document / reference managers with growing AI features:
How gknowledge differs
- Native to GNOME, not Electron/Tauri or web-first — GTK 4 + Libadwaita, HIG-aligned, Flatpak-friendly.
- Offline-first and provider-agnostic — a local heuristic engine ships in the box; OpenAI-compatible endpoints (OpenAI, Ollama, LM Studio, vLLM, OpenRouter, …) are optional, swappable, and configured per project.
- Inspectable, user-owned format — knowledge is plain Markdown with YAML frontmatter (Obsidian-compatible) plus a readable SQLite index; nothing is locked behind a sync service.
- Incremental, not stateless RAG — sources are ingested once into a persistent, cross-linked knowledge space with provenance, rather than re-retrieved from scratch on every question.
- Human-in-the-loop — generated content is clearly marked and a review queue keeps you in editorial control.
Project docs
ROADMAP.md— milestones and the features we are borrowing from peersTODO.md— actionable backlogDISTRIBUTING.md— positioning and distribution study of comparable projects (Italian)CONTRIBUTING.md— how to contributedocs/DESIGN.md— the original product and design documentCHANGELOG.md— what changed in each release
License
MIT. Contributions are welcome, see CONTRIBUTING.md.
Star history
If gknowledge is useful to you, a star helps other GNOME users find it.
gknowledge MCP 질문
gknowledge MCP를 Claude Code에 추가하려면 어떻게 하나요?
터미널에서 claude mcp add gknowledge -- uvx gknowledge-mcp를 실행합니다. 모든 프로젝트에서 사용할 수 있게 하려면 --scope user를 추가합니다.
gknowledge MCP를 Cursor에 추가하려면 어떻게 하나요?
~/.cursor/mcp.json를 열고 mcpServers 아래에 서버를 추가합니다. 위 설치 섹션에 표시된 Cursor 구성을 사용합니다.
gknowledge를 사용하려면 API 키가 필요한가요?
아니요, 기본적으로 내장된 휴리스틱 엔진을 통해 오프라인으로 작동합니다. 다만, 원하는 경우 OpenAI 호환 엔드포인트에 연결할 수 있습니다.
위키가 Obsidian과 호환되나요?
네, wikilink와 YAML frontmatter를 사용하는 일반 Markdown을 사용하므로 해당 폴더를 Obsidian에서 그대로 사용할 수 있습니다.