Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Cross-session memory for AI agents with a Source Receipt for every memory, over MCP.
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.
Authorization비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.
터미널에서 이 명령어를 실행하세요
claude mcp add --transport http memory https://cairn.ink/api/mcp --header 'Authorization: your-value'실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"memory": {
"url": "https://cairn.ink/api/mcp",
"headers": {
"Authorization": "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": {
"memory": {
"type": "http",
"url": "https://cairn.ink/api/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 주소는 요청 header에 키가 필요한데, 커넥터 추가 메뉴에서는 넣을 수 없어요. 대신 Claude Code, Cursor, VS Code를 쓰세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
Authorization 비밀 HTTP header이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 도메인 cairn.ink 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
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.
입력해야 할 값: Authorization
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.0)은 42일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
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.
Cairn Memory
Keep important context between AI sessions. Change it when things change.
English · 繁體中文
See an example · Where to start · Local setup · Hosted setup · Limitations · Privacy
Cairn Memory is Cairn.ink's open-source AI memory toolkit for Claude Code and Codex, with local MCP tools or cloud automatic memory. Visit Cairn.ink, install @cairn-ink/memory on npm, or view the Cairn Memory GitHub repository.
Starting a new AI session often means repeating your preferences and project decisions. Cairn provides memory tools to save that context between sessions, inspect the submitted text behind each memory, and update it when things change.
Suppose you save “Keep my reports short.” Later, you decide you need detailed reports. You can inspect the old memory and its source text, correct the saved preference, or forget it so it is no longer available for active recall.
This is an illustrated explicit-tool example, not a chat-client screenshot. The local preview uses tools to save, inspect, correct and forget; it does not automatically read your conversations.
A Source Receipt is the submitted text attached to a memory. It helps you check what was supplied when the memory was saved or corrected. It is not a verified transcript of the whole conversation or proof of human intent.
Cairn Memory is the open-source toolkit in this repository for saving, inspecting and changing AI memory. [Cairn](https://cairn.ink) is the hosted shared memory map for people and AI, where people organize, review and share knowledge.
This repository includes local memory tools and connectors to the hosted Cairn service. Each path has its own setup and feature boundaries. Local use does not require a Cairn account; hosted connections require a compatible service and authentication.
| You want to… | Start here | What you need |
|---|---|---|
| Understand the idea before installing | 繁體中文 or the recorded walkthrough | No installation or account |
| Try the open-source tools on your computer | Local preview setup or Windows guide | Terminal setup; Linux x64 and a bounded native Windows x64 check; no Cairn account |
| Use the documented hosted Claude Code or Codex connection | Hosted setup | A compatible hosted service and authentication; separate from local-preview client support |
| Build on the memory layer | Architecture and MCP tools | JavaScript or MCP integration work |
If you use Claude or Codex but do not usually install tools from a terminal, start with the example and recorded walkthrough. This preview requires setup; check the tested client paths before connecting your AI tool.
Cairn's open-source memory layer stores memories in your own SQLite file and exposes them through MCP or JavaScript. No Cairn account is needed for local use.
Developer preview. Installed persistence and a narrow real-model memory loop have retained evidence. Default extraction still fails our source-support bar; see known limitations. Save, inspect, correct and forget work without a model key. Semantic recall requires your OpenAI key and sends selected context to that provider.
Watch the 36-second model-free demo (MP4). This records the memory tools running, rather than a conversation in Claude or Codex. “Model-free” means no AI model is called during the walkthrough.
For long-conversation results, see the four-case real-model pilot. It is an opt-in diagnostic with one failed Cairn answer, not a measurement of long-term default-client recall reliability. Known limitations
Open the recorded tool walkthrough (GIF)
The demo below records the model-free loop: save, restart, inspect, correct and forget. Its recall step reports model_not_configured.
Recorded responses and regeneration instructions · Verified capabilities and client support
For Claude Code and Codex, run the one-command installer:
npx @cairn-ink/memory setup
A fresh interactive install asks once: local MCP memory tools on this computer, or cloud automatic memory with cairn.ink sign-in; choose directly with setup --local or setup --cloud. Fresh non-interactive runs need --local or --cloud; local mode has no automatic capture or recall in 0.6.3.
Installer 0.6.3, with Codex 0.164.0–0.166.0 format requalification, was published on 2026-11-03, so npx @cairn-ink/memory setup uses it; a checkout can also run node packages/setup/bin/memory.mjs setup. The plugin is 0.3.3. Requires Node ≥22.16 and at least one CLI on PATH. Cloud setup asks about new tools, updates connected tools, and uses one browser sign-in when connecting both. The default server is cairn.ink. Conflicting servers or memory IDs present a choice; non-interactive conflicts change nothing. Codex must pass format qualification before automatic memory is enabled. Automated codex exec runs skip capture and prompt recall by default; opt in with npx @cairn-ink/memory config --codex-capture-exec on.
Choose the mode that fits your workflow:
Prerequisites: Git, Node >=22.16, npm and `tar`. Recorded checks cover Linux x64 and a bounded native Windows x64 installation. On Windows, use the [PowerShell setup and walkthrough](docs/windows-install.md); the commands below use Linux/WSL paths. Other platforms are unverified. Install from this repository: the unscoped npm and PyPI packages named cairn-memory are unrelated projects. The local archive is not published to npm yet.
1. Install into a new directory. Replace the path below with a new absolute directory beneath an existing parent you control.
git clone https://github.com/Cairn-ink/cairn-memory.git
cd cairn-memory npm run install:preview -- --directory /absolute/new/cairn-local --owner local-user
The installer builds this checkout and downloads pinned public npm dependencies without install scripts. It creates app/, data/ and a private installation-receipt.json containing the executable path and MCP settings. It makes no model calls. Keep the receipt private: it contains local paths and identity. Installation details, recovery and backup
2. Run the model-free check. From the source checkout, use the same installation path. No chat-client setup or model key is needed.
npm ci --prefix adapters/mcp
node adapters/mcp/walkthrough.mjs --executable /absolute/new/cairn-local/app/node_modules/.bin/cairn-memory
Expect status: "passed". The check uses a fresh synthetic database and verifies the five tools, receipts, process-restart persistence, correction and forgetting. It strips the model key from the child process; model_not_configured is the expected recall result. Steps and expected results
3. Connect a client. Copy stdio.command and stdio.args from your private installation receipt into the client's local MCP configuration. Keep the same database, owner and project across sessions. See the tested client matrix.
For semantic recall, explicitly supply OPENAI_API_KEY through the MCP process's secret environment. The walkthrough's optional --with-recall path sends synthetic context to OpenAI and incurs model charges; it has no built-in dollar cap. A fully local model path is not yet verified.
For the Hermes native provider, follow its separate setup guide. It uses a profile-local database and owner, plus CAIRN_MEMORY_OPENAI_API_KEY, rather than the generic MCP settings above.
| Tool | Purpose |
|---|---|
remember_memory | Explicitly save one memory and its receipt |
recall_memory | Model-guided retrieval of current memories and receipts |
inspect_memory | List memories, or inspect an ID, revision and receipts |
correct_memory | Replace content at the revision you inspected |
forget_memory | Logically delete at the revision you inspected |
The default local server exposes explicit tools. For opt-in submitted-message capture, project scope and configuration checks, see the installed preview guide. The full evidence and limitations cover extraction failures, long-history retrieval and the boundaries of individual client tests.
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요