原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Warn MCP

作者:APVentureEngine版本 0.2.6i★ –i电脑或云端
注册名称io.github.APProj/warn-mcp

安装

概览

作者提供的说明(英文原文)

Search 61,428+ US WARN Act layoff notices: 48 states, 1988-today, daily. Bundle needs no API key.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 电脑或云端
  • 传输方式: stdio, Streamable HTTP
  • 分类: 搜索与 AI 记忆
  • 你需要填写:Authorization

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。

下载作者的 .mcpb 文件

链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。

在终端中运行这条命令

claude mcp add --transport http warn https://mQpACuIiQcnwK93JY.apify.actor/mcp --header 'Authorization: your-value'

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "warn": {
      "url": "https://mQpACuIiQcnwK93JY.apify.actor/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "warn": {
      "type": "http",
      "url": "https://mQpACuIiQcnwK93JY.apify.actor/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • Authorization 机密 必填 HTTP header
    Bearer - required by the Apify platform, which meters the compute to YOUR free account. We charge nothing and store nothing. Prefer the stdio .mcpb package above if your client supports it: that one…

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ! 注意

    作者与仓库一致

    发布者(APProj)不是仓库所有者(APVentureEngine);可能是其他人代为上架的

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7249 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7249 个服务器的 48% 更新
  • 基础检查结果等于或优于此分类中其他 7249 个服务器的 33%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Warn MCP 安全吗?

它在 1 项适用的基础检查中通过了 0 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:Authorization

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.6)于43天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT今天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

warn-mcp — US layoff data (WARN Act) as an MCP server

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?"*

Install

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" } } }

Hosted: a URL, no install (ChatGPT / Claude.ai connectors, n8n, any remote client)

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.

Or run it over HTTP (Streamable HTTP transport)

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

-> http://localhost:8080/mcp (and a short human page at http://localhost:8080/)

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.

Tools

ToolWhat it answers
search_layoff_noticesEmployer / state / date-range / minimum-headcount search across the whole archive. Returns matched notice count, total workers affected, and the newest matches.
latest_layoff_noticesThe rolling ~14-day feed of newly published notices, newest first, optionally one state.
employer_layoff_historyOne employer's whole WARN record back to 1988 — notices, workers affected, every state it filed in, first and latest activity.
state_layoff_totalsMonthly notice counts and workers affected: a national leaderboard by state, or one state's month-by-month series.
agency_revisionsThe 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_statusLast 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.

Why an MCP server and not just the CSV

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).

Caching and network

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, license, attribution

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).

The one paid thing

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.

问 PopNx