Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Issue tracker and durable project memory for your coding agent, scoped to the folder you open.
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.
TRAIL_API_URL, TRAIL_PROJECT필요한 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": {
"trail": {
"command": "npx",
"args": [
"-y",
"usetrail"
],
"env": {
"TRAIL_API_URL": "your-value",
"TRAIL_PROJECT": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add trail --env TRAIL_API_URL=your-value --env TRAIL_PROJECT=your-value -- npx -y usetrail실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"trail": {
"command": "npx",
"args": [
"-y",
"usetrail"
],
"env": {
"TRAIL_API_URL": "your-value",
"TRAIL_PROJECT": "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": {
"trail": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"usetrail"
],
"env": {
"TRAIL_API_URL": "your-value",
"TRAIL_PROJECT": "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.
TRAIL_API_URL envTRAIL_PROJECT 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 6일 점검
게시자(usetrail.dev)가 저장소 소유자(arsprengel)가 아니에요. 다른 사람이 등록했을 수 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 0개를 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(1.29.1)은 2개월 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
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
The MCP server for [Trail](https://usetrail.dev) - it gives your coding agent your team's tracker and the project's durable memory, scoped to the folder you have open.
Your agent stops working blind. It reads what is open, writes what it did, and records what it learned the hard way - in the same board your team looks at, not in a scratch file that only that session can see.
This package is the client. It talks to your Trail account over the REST API; there is no database here. Dependencies are @modelcontextprotocol/sdk, zod and the built-in fetch.
# 1. connect this machine to your Trail account (opens your browser; no token to copy)
npx -y usetrail@latest login
claude mcp add trail -s user -- npx -y usetrail@latest
No account yet? Create one at usetrail.dev - the free plan covers three projects and three people.
Not tied to one agent. This is a plain MCP server over stdio, speaking the three protocol versions in use today. Any MCP-compatible client can run it; only the registration command differs, and each client documents its own.
Prefer a local checkout? Clone it instead, and the connector keeps itself up to date on its own (see Updating):
git clone https://github.com/arsprengel/trail-mcp.git ~/.trail-mcp
npm --prefix ~/.trail-mcp install --omit=dev node ~/.trail-mcp/bin.js login claude mcp add trail -s user -- node ~/.trail-mcp/bin.js
On Windows, write the real path instead of ~: the registration stores the argument verbatim and Node does not expand it.
The tracker - list_items, get_item, add_item, update_item, move_item, get_next, delete_item. Real items on your team's board, with type, status, priority, assignees and history. Work the agent picks up shows as in progress and closes when it is done, so the board is not a story someone has to retell.
Project memory - list_memory, get_memory, add_memory, update_memory, review_memory. The durable knowledge of a project: the deploy that has a trap in it, the decision nobody should relitigate, the command that is not in any README. Shared by everyone on the project, human or agent. A new session reads it before acting instead of rediscovering it.
Reminders - add_reminder, list_reminders, update_reminder, delete_reminder. Things with a date that must not be silently missed - and the agent closes or reschedules them itself once the date arrives.
Attachments - add_attachment, get_attachment. Files that belong to an item.
Trail holds many projects. The connector uses the folder you have open as the project - the folder name, or whatever a .trail file next to it says, or the TRAIL_PROJECT variable. So the agent writes to the right project without being told, and two repositories never bleed into each other. To reach across, the agent passes project explicitly on the tool.
Installed for you, once, when you log in - and on the connector's first run, which covers people who paste a token into the registration instead of logging in through the browser. Every session that starts in a project with a tracker gets the open items and the project memory in context from the first message - the agent starts knowing, instead of depending on someone remembering to ask. Fail-silent by design: no login or no network and the hook stays quiet.
Each tool keeps this in its own place, so the connector writes to the one that tool actually reads:
~/.claude/settings.json.~/.gemini/settings.json.~/.gemini/config/mcp_config.json, which is the file it actually reads: `gemini mcp add` does not connect Trail in Antigravity, because that command writes to ~/.gemini/settings.json instead. Field-tested on Antigravity 2.11 (Windows), of the three things that live in that config folder only the tool registration is honored - the opening-summary hook is not run, and a plugin folder placed exactly where its own documentation says is not read. So on Antigravity the agent gets the tools and the server's working rules, and fetches the project summary itself on the first turn instead of receiving it. The plugin path is built and tested behind a switch, waiting for that to change.usetrail status tells you, per tool found on this machine, whether it is on - so you never have to go digging through settings files to find out.
It never fights you. A tool that isn't on the machine gets nothing created for it, and hooks install will not fabricate a config for a program you don't have. If you remove it with hooks uninstall, it does not come back on its own - put it back with:
npx -y usetrail@latest hooks install
Clients without a hook mechanism are covered too: the server's own instructions tell the agent to fetch the summary itself before acting.
Point it at your server once and it stays pointed:
TRAIL_API_URL=https://your-trail npx -y usetrail@latest login
Without that variable, login goes to the hosted service.
npx -y usetrail@latest # start the MCP server over stdio - what your agent runs
npx -y usetrail@latest login # connect this machine (browser confirmation, no token copying) npx -y usetrail@latest status # server address, current project, whether a token is present npx -y usetrail@latest logout # delete the saved token npx -y usetrail@latest doctor # find the install on this machine and unstick auto-updates
The token is stored at ~/.config/trail/token.json (mode 600). Revoke it whenever you want from the "AI token" panel in the app.
| Variable | What it does |
|---|---|
TRAIL_API_URL | Your own Trail's address. Saved after the first login. Defaults to the hosted service. |
TRAIL_PROJECT | Forces the project name (default: the open folder). |
TRAIL_API_TOKEN | A token directly, skipping the browser login. Useful in CI. |
TRAIL_LANG | Language of what the connector prints on screen: pt or en. Without it, your system's language, and English when your system states none. Never changes what the agent reads. |
The former names (TETHER_*) keep working, with no deadline - the product used to be called Tether, and nothing anyone already configured has to change.
The `@latest` is not decoration. Registered as npx -y usetrail@latest, the connector resolves the published version every time your agent starts a session, so a new release reaches you without anyone doing anything. Registered as bare npx usetrail, npm reuses whatever copy it cached the first time - and that machine stays on that version forever. Use @latest.
The cost of @latest is about a second at session start, and a network call. Neither matters in practice: the connector talks to Trail over the network anyway.
A cloned install updates itself differently: on startup it fires a quiet fast-forward pull in the background, at most every six hours. The running session keeps the version it loaded; the next one starts updated. No network or a local conflict and nothing happens, silently.
Stuck on an old version? npx -y usetrail@latest doctor finds the install, reports the version and unsticks it.
Node 18 or newer.
MIT. This package is the client - the connector you run on your own machine. Use it, fork it, adapt it. The Trail service it talks to is a separate, hosted product.