Context7
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제작자가 쓴 설명(영어 원문)
Search 61,428+ US WARN Act layoff notices: 48 states, 1988-today, daily. Bundle needs no API key.
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.
링크는 제작자의 파일로 바로 연결돼요. 우리가 보관하거나 다시 패키징하지 않아요. 파일을 열면 Claude Desktop이 설치해요.
터미널에서 이 명령어를 실행하세요
claude mcp add --transport http warn https://mQpACuIiQcnwK93JY.apify.actor/mcp --header 'Authorization: your-value'실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"warn": {
"url": "https://mQpACuIiQcnwK93JY.apify.actor/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": {
"warn": {
"type": "http",
"url": "https://mQpACuIiQcnwK93JY.apify.actor/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 필수 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
게시자(APProj)가 저장소 소유자(APVentureEngine)가 아니에요. 다른 사람이 등록했을 수 있어요
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 0개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: Authorization
둘 다 가능해요. 내 컴퓨터에 설치해도 되고, 클라우드 버전에 연결해도 돼요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.2.6)은 43일 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
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
61,428 mass-layoff notices · 48 states · 1988 → today · rebuilt every morning · no API key · zero dependencies.
Every US state publishes the layoff notices employers must file under the WARN Act, and every state publishes them differently — a web page here, a pile of PDFs there, a search form somewhere else. WARN Feed scrapes all 48 of them daily and normalizes them into one schema. This is that dataset wired into the Model Context Protocol, so Claude, Cursor, Continue or your own agent can ask questions like:
*"Has Starbucks filed any WARN notices this year, and in which states?"*
*"What layoffs were announced in the last two weeks in Texas?"*
*"Which state had the most workers affected in 2026?"*
*"Did any agency quietly change or delete a notice this week?"*
Nothing to build and nothing to install into your Python environment — the server is standard library only.
Claude Desktop — one file, no terminal: download warn-mcp.mcpb and drag it onto Claude Desktop's Settings → Extensions window. That bundle is this repo's server plus a manifest; it needs a python3 on your PATH and nothing else. The same file is listed as the installable package for io.github.APProj/warn-mcp in the MCP registry.
Claude Desktop / Claude Code / anything that reads an `mcpServers` block:
{
"mcpServers": { "warn": { "command": "uvx", "args": ["--from", "git+https://github.com/APVentureEngine/warn-mcp", "warn-mcp"] } } }
Claude Code, one line:
claude mcp add warn -- uvx --from git+https://github.com/APVentureEngine/warn-mcp warn-mcp
No uv? Clone and run it with plain Python:
git clone https://github.com/APVentureEngine/warn-mcp && cd warn-mcp
python3 -m warn_mcp.server --selftest # exercises every tool against live data
{
"mcpServers": { "warn": { "command": "python3", "args": ["-m", "warn_mcp.server"], "cwd": "/path/to/warn-mcp" } } }
If your client wants a remote MCP server rather than a subprocess, point it at:
https://mQpACuIiQcnwK93JY.apify.actor/mcp (Streamable HTTP)
Same six tools, same daily-rebuilt data, same code as this repo. One honest caveat: the host (Apify) requires the *caller's* own API token, because it meters the compute to the account that calls it. Create a free Apify account, copy your token, and send it as Authorization: Bearer . We charge nothing, we see nothing, and we store nothing about your queries. If your client supports stdio, the .mcpb bundle above needs no token at all and is the better route.
claude mcp add --transport http warn https://mQpACuIiQcnwK93JY.apify.actor/mcp \
--header "Authorization: Bearer "
This endpoint is also listed as the remotes entry for io.github.APProj/warn-mcp in the official MCP registry.
The same six tools, same implementation, spoken over MCP's Streamable HTTP transport instead of stdio — for clients that want a URL rather than a subprocess, and for putting one shared instance behind your own team:
docker build -t warn-mcp . && docker run -p 8080:8080 warn-mcp
claude mcp add --transport http warn http://localhost:8080/mcp
No Docker? python3 http/app.py does the same thing — it is standard library only, like everything else here. PORT selects the port, /healthz returns {"ok":true}, and the server is stateless, so you can run as many replicas as you like behind any load balancer.
It is deliberately keyless: the data underneath is public and read-only, the server keeps no session state and stores nothing about callers. Do not bolt auth onto a public deployment of it and then advertise it as this server.
| Tool | What it answers |
|---|---|
search_layoff_notices | Employer / state / date-range / minimum-headcount search across the whole archive. Returns matched notice count, total workers affected, and the newest matches. |
latest_layoff_notices | The rolling ~14-day feed of newly published notices, newest first, optionally one state. |
employer_layoff_history | One employer's whole WARN record back to 1988 — notices, workers affected, every state it filed in, first and latest activity. |
state_layoff_totals | Monthly notice counts and workers affected: a national leaderboard by state, or one state's month-by-month series. |
agency_revisions | The dataset's own change log: a field-level diff of consecutive daily builds — amended fields (headcounts, dates, locations…), row_absent notices, row_returned ones — each tagged with a mechanically-determined cause_class. Records the observation, not the cause. |
dataset_status | Last rebuild time, states flagged stale, license, and the raw endpoints — call it before quoting a number. |
Every answer carries as_of and source, because a layoff figure with no date and no attribution is not worth repeating. Where the data is weaker than it looks, the tool says so in a caveat field rather than letting the model round it off: headcount is only counted where the agency published one, employer names are normalized by an auditable rule table rather than a corporate-registry join, and row_absent in the revision log means the agency stopped publishing a notice — not that the layoff was cancelled.
The CSV is right there and it is free — take it. This exists for the case where a model needs one specific answer out of a 9 MB file: the tools do the filtering and the arithmetic locally, so an agent spends a few hundred tokens instead of a context window, and it gets the freshness stamp with the answer.
agency_revisions is the part you cannot reconstruct from any single copy of the data. A state agency editing its own WARN page leaves no changelog, so a mirror taken today simply *is* today's truth. WARN Feed diffs yesterday's build against today's and keeps the field-level log — 638 logged changes since 2026-08-31, including 274 notices that stopped appearing. One honest caveat, stated in every response: a logged change can come from the agency amending or withdrawing a notice *or* from an improvement to this project's parser, and the log does not guess which — cause_class labels only what is mechanically distinguishable (field_populated, field_cleared, format_only, value_changed, unknown).
Tools read the free public WARN Feed endpoints over HTTPS and cache them on disk (~/.cache/warn-mcp, override with WARN_MCP_CACHE) with ETag revalidation, so ten tool calls in a row make at most one request per file per hour (WARN_MCP_TTL, seconds). If the network is down and a cached copy exists, the cached copy is served and its own as_of tells you how old it is.
There is no key, no signup, no rate limit and no telemetry — this server sends nothing anywhere except plain GETs for public files.
Data is compiled from official state WARN publications and released under CC BY 4.0 — credit "WARN Feed" and link back. This server's code is MIT. Not affiliated with any state agency or the US Department of Labor; state agencies' own postings are the authority and are occasionally revised (see agency_revisions).
Everything above is free and stays free. If you need to be *told* — your own list of employers matched against every daily refresh and pushed to a private alert page, a calendar feed, or a private RSS feed you point Slack, Discord or Teams at — that is WARN Watch, $49/year, with a free 30-day trial and no card. It is the only thing here that costs money.
Bugs, a state we should cover, a tool you want: open an issue.