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제작자가 쓴 설명(영어 원문)
Task spine + searched dead ends + approvals for AI coding agents. One brain, every device.
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.
필요한 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": {
"shinobi": {
"command": "npx",
"args": [
"-y",
"@shinobiapps/shinobi"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add shinobi -- npx -y @shinobiapps/shinobi프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"shinobi": {
"command": "npx",
"args": [
"-y",
"@shinobiapps/shinobi"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"shinobi": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@shinobiapps/shinobi"
]
}
}
}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.
이 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 numbererikson 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(0.3.1)은 5개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: GitHub, Desktop Commander, Cloudflare MCP
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
The task spine for AI coding agents. Shinobi holds the decisions that survive across sessions, actively searches your past dead ends — semantically — before the agent writes code, and routes approvals to your phone. One brain, every device: laptop, cloud session, and mobile all wired to the same store.
Works with Claude Code, Cursor, Cline, Continue.dev, Zed — any MCP-compatible client.
Status: v0.3 — autonomous agents. Run it as a hosted HTTP
/mcpbrain (the default deploy) or self-host a local instance. Mobile push, a headless dispatch loop, parallel swarm over git worktrees, and audit→subtask ingestion on top of the remote MCP foundation. 39 MCP tools, web dashboard, mobile approvals, plugin system, optional semantic recall.
Most tools try to be a memory bolt-on. Shinobi is the task spine your agent works *along* — the durable backbone of work, decisions, and known-bad paths that outlives any single session and follows you across every device.
request_approval pushes the decision to your pocket; the agent blocks until you tap yes/no, wherever you arelink_commit ties commits to subtasks via [SHI-N] tags or via target_path attribution.js file in ~/.shinobi/plugins/ or install a @shinobi/plugin-* npm package and register custom plugin_* toolsHosted or self-hosted, your call. The default deploy is one remote brain behind an HTTP /mcp endpoint (we run ours at shinobi.shinobi-apps.com); the same binary still runs as a fully local single-machine instance when you'd rather keep everything on your own box. BYO embedding provider only if you want semantic recall.
🚀 New here? Follow Getting started — zero to a
working brain in ten minutes. Going multi-device? Remote mode
+ $0/month cloud deploy.
Requirements:
PATHbetter-sqlite3 native build (most systems have prebuilt binaries; Windows may need Visual Studio Build Tools as fallback)npm install -g @shinobiapps/shinobi
The binary is shinobi (e.g. shinobi serve, shinobi dashboard).
npm install -g github:numbererikson/shinobi
Pulls from main. Useful for trying unreleased fixes. On Windows you may need to add your Node directory to system PATH before this works, because the prepare build script runs in a subshell that does not always inherit per-session PATH (Laragon, portable installs). If install fails with 'node' is not recognized, prefer the npm install above.
git clone https://github.com/numbererikson/shinobi.git
cd shinobi npm install # triggers prepare → builds dist/ npm install -g .
In any project root where you want Shinobi available to your MCP client:
shinobi init
shinobi dashboard
init will:
~/.shinobi/ with config.json, .env template, and shinobi.db (migrations applied).mcp.json snippet for the current projectshinobi init writes config for the two clients with a workspace-local MCP convention out of the box:
/.mcp.json /.cursor/mcp.jsonRestart the client and the mcp__shinobi__* tools become available.
For other MCP clients (Cline, Continue.dev, Zed), see the MCP client setup section below.
Then open:
http://127.0.0.1:8765
On Windows PowerShell, if script execution blocks shinobi, use the .cmd shim:
shinobi.cmd dashboard
If you upgraded Node or copied an old node_modules, rebuild native dependencies:
npm rebuild better-sqlite3
Important: the code lives in the Shinobi folder, but the local memory database lives in:
~/.shinobi/shinobi.db
To move the tool only, copy/clone the Shinobi folder and run the install commands above. To move the existing projects, tasks, decisions, notes, and context too, either copy ~/.shinobi/ or use shinobi sync.
Every snippet below uses the same JSON shape — command is the path to the Node binary that's running Shinobi, args is [ , "mcp"]. Print the exact values for your machine:
shinobi init --print-config
(Or read .mcp.json from any project where you already ran shinobi init — the values are identical.)
Drops in automatically — shinobi init writes /.mcp.json. Restart Claude Code to pick up the server.
Drops in automatically — shinobi init writes /.cursor/mcp.json. Works on Cursor 0.43+. Restart Cursor or reload the workspace.
For a global Cursor config (every project sees Shinobi), paste the same snippet into ~/.cursor/mcp.json (or use Cursor Settings → MCP).
Open Cline's settings file:
%APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.jsonMerge the contents of your project's .mcp.json into the file's mcpServers object. Restart VS Code.
Edit ~/.continue/config.json. Add Shinobi to the mcpServers array (note: Continue uses an array, not an object like the others):
{
"mcpServers": [ { "name": "shinobi", "command": "/absolute/path/to/node", "args": ["/absolute/path/to/dist/cli.js", "mcp"] } ] }
Use the values from your project's .mcp.json for command and args.
Edit ~/.config/zed/settings.json. Zed nests MCP servers under context_servers:
{
"context_servers": { "shinobi": { "command": { "path": "/absolute/path/to/node", "args": ["/absolute/path/to/dist/cli.js", "mcp"] } } } }
Restart Zed.
Any MCP client that supports the standard { command, args } server spec should work. Use the same values your .mcp.json has:
command: absolute path to the Node binary running Shinobiargs: [ , "mcp"]Avoid the bare shinobi command in MCP config — many clients spawn servers with shell: false, which skips the OS PATH resolution that makes shinobi work in a terminal.
Host one Shinobi brain on a server and connect every device to it — your desktop editor, Claude Code web/mobile sessions, any remote-MCP-capable client. shinobi serve exposes the MCP endpoint at /mcp (streamable HTTP, stateless, bearer-token auth) alongside the dashboard:
claude mcp add --transport http shinobi https://your-host/mcp \
--header "Authorization: Bearer YOUR_TOKEN"
This is the recommended way to run Shinobi — one brain, reachable from every device. The same binary still runs as a local single-machine instance if you'd rather self-host everything on your own box. Full deployment guide (Docker, Cloudflare Tunnel, GCP Always Free, client config): docs/remote-mcp.md.
shinobi <command> [options]
Commands: init Bootstrap ~/.shinobi/ and drop .mcp.json in the current directory mcp Run the MCP server over stdio (invoked by the MCP client) migrate Apply pending SQL migrations dashboard Start the web dashboard on localhost (default port 8765) serve [--host H] [--port P] Dashboard + MCP HTTP endpoint (/mcp) in one process — see docs/remote-mcp.md sync init [branch] Configure a local git repo as the cross-machine sync target sync push Snapshot the DB and commit it to the sync repo sync pull Restore the DB from the sync repo's snapshot sync status Show last push/pull timestamps and git status dispatch [--once|--drain] Autonomous loop: pull next_task → run worker → complete/unblock → repeat [--project N] [--interval S] [--max-failures N] Worker via SHINOBI_WORKER_CMD (e.g. 'claude -p "$SHINOBI_TASK_PROMPT"'); unset → dry-run swarm --agents N N dispatch loops in parallel, each in its own git worktree/branch, one shared [--project N] [--drain] brain. Atomic claim → no two agents take the same task. --no-worktree / --keep-worktrees
| Group | Tools |
|---|---|
| Projects | list_projects, get_project, create_project, update_project, archive_project, unarchive_project, delete_project |
| Subtasks | list_tasks, get_task, create_task, bulk_create_tasks, update_subtask, delete_subtask, claim_task, complete_task, next_task |
| Decisions | log_decision, decisions_for_file, update_decision_status |
| Dead ends | log_dead_end, check_dead_ends |
| Notes | add_note, list_notes |
| Plans | save_plan, get_plan |
| Context | get_context, update_context |
| Recall | recall (FTS5 or semantic) |
| Timeline | history, link_commit |
| Workflow | agent_bootstrap, session_closeout, file_context |
| Extraction | extract_decisions, compress_session_summary |
| Approvals | request_approval |
| Notifications | notify |
| Findings | ingest_findings |
| Plugins | plugin_hello |
| Layer | Tech |
|---|---|
| Language | TypeScript (strict mode, ES2022, NodeNext) |
| Runtime | Node 18+ |
| MCP | @modelcontextprotocol/sdk 1.x |
| Storage | SQLite via better-sqlite3 (WAL mode) |
| Dashboard | Hono + @hono/node-server (same process, localhost:8765) |
| Embeddings (optional) | OpenAI text-embedding-3-small / Voyage voyage-3-lite / Ollama nomic-embed-text |
| Migrations | Forward-only, sha256 checksum, schema_migrations table |
See docs/architecture.md for the r
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요