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。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Verity

作者:veritylabsai版本 0.2.0i★ –i在云端运行
注册名称io.github.veritylabsai/verity

安装

概览

作者提供的说明(英文原文)

Cited product-compliance ground truth for AI agents. Never generates; always cites.

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: 在云端运行
  • 传输方式: Streamable HTTP
  • 分类: 法律与政府数据

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

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 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://verity-mcp-243195959173.us-central1.run.app/mcp

在终端中运行这条命令

claude mcp add --transport http verity https://verity-mcp-243195959173.us-central1.run.app/mcp

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": {
    "verity": {
      "url": "https://verity-mcp-243195959173.us-central1.run.app/mcp"
    }
  }
}

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": {
    "verity": {
      "type": "http",
      "url": "https://verity-mcp-243195959173.us-central1.run.app/mcp"
    }
  }
}

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。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://verity-mcp-243195959173.us-central1.run.app/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

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

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 veritylabsai 验证,该账户拥有此仓库

  • … 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“法律与政府数据”中的其他服务器比较i

  • 星标数多于此分类中其他 1731 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1731 个服务器的 41% 更新
  • 基础检查结果等于或优于此分类中其他 1731 个服务器的 100%

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

Verity 安全吗?

它在 1 项适用的基础检查中通过了 1 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?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.0)于2个月前进入注册中心。

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:Agent Data Tools: Company, compliance and checks, Agent Data Tools, Private Law Wiki

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

Agent Data Tools

作者:Nutshell2000

641 agent tools: chain data, prices, sanctions, web, PDF. 25 free calls, then from $0.002.

在云端运行今天更新
安装

Private Law Wiki

作者:privatelawattorneys

Sourced answers, search and bank-case assessment for wiki.private.law by the Mothership runtime.

在云端运行今天更新
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。

US product recall lookup for AI agents — CPSC consumer products and FDA food, drug and device enforcement, with every result pinned to an official source.

The point is not that it searches; it is that it refuses to answer without a citation. Ask it something it has no record of and it says so, rather than inventing a plausible answer.

Live API: https://rattlewatch.rattled.ca MCP endpoint: https://rattlewatch.rattled.ca/mcp Interactive docs: https://rattlewatch.rattled.ca/docs

Machine-readable discovery, for agents rather than browsers:

DocumentURL
llms.txt/llms.txt
MCP server card/\.well-known/mcp/server.json

One container serves both surfaces — the REST API and MCP over streamable HTTP at /mcp. That matters for registry discovery: directories introspect the image's default command, so it has to be a working MCP server.

curl "https://rattlewatch.rattled.ca/v1/recalls/search?q=Bistro%20Pro%20Electric%20Grill"

Rattlewatch answers the questions an agent cannot safely answer itself:

  • *Is this product, brand, or model number subject to a recall?*
  • *Which agency published that recall, and where is the source?*
  • *What recalls or rule changes appeared since a given date?*

Every answer carries an official source URL and a last-verified date. Rattlewatch never generates an answer — it returns records that exist in its store, or it says *"no verified record"*. Absence is an honest negative, not a guess.


The trust guarantee

An answer without a citation does not ship.

  • Cited — every fact and recall is pinned to an official source (CPSC, EUR-Lex, ECHA, the European Commission, OEHHA).
  • Versioned — facts are append-only. A changed answer creates a new version and a change event, never an in-place edit.
  • Current — the store is re-verified against its upstream sources on a schedule; verified_at tells you exactly when.
  • Non-generative — verify() returns only matching records. If nothing matches, it returns found: false with an explicit reason. It will not invent one.

Tools (MCP)

ToolWhat it returns
search_recallsCited recall records matching a product name, brand, model, or UPC
get_requirementCited compliance requirements for a subject + market
list_changesThe change feed: new recalls and rule changes since a timestamp
verifyCited records matching a claim/query, or an explicit no verified record

Data coverage

  • Recalls — the full structured U.S. CPSC feed (consumer products) plus openFDA enforcement reports for food, drug and device. Every record carries a resolvable source URL: the official CPSC page, or a per-record openFDA query.
  • Requirements — a small curated set of cited market-entry facts, seven in total: CPSIA/Children's Product Certificate, CPSC eFiling, EU GPSR, CE marking, REACH SVHCs, RoHS, and California Prop 65 — each with a verbatim citation. This is a companion to the recall data, not a regulatory database.
python -m rattlewatch build --max-recalls 5000 --fda-limit 3000   # default in the image

python -m rattlewatch build --fda-limit 0 # CPSC only (used by CI)

The engine is domain-agnostic: new markets (UK, CA, AU, JP, and beyond) and new rule sets are added as more cited facts and feeds are compiled, without code change.


Quick start

python -m venv .venv && .venv/Scripts/activate   # or: source .venv/bin/activate

pip install -r requirements.txt

build the store (facts + CPSC recalls)

python -m rattlewatch build

run as an MCP server over stdio (local agents)

python -m rattlewatch mcp

or serve the REST API + MCP over HTTP

python -m rattlewatch serve --host 0.0.0.0 --port 8000

Connect a client
{

"mcpServers": { "rattlewatch": { "command": "python", "args": ["-m", "rattlewatch", "mcp"], "cwd": "/path/to/rattlewatch" } } }


REST API

EndpointTier
GET /v1/recalls/search?q=...Free (rate-limited)
GET /v1/requirements?subject=...&market=...Free
GET /v1/changes?since=...Free
POST /v1/verifyFree
GET /v1/premium/exportMetered — returns HTTP 402 with an x402 payment requirement

Interactive docs: /docs.

Pricing

Free discovery and lookups, metered premium calls. The premium endpoint implements the x402 payment flow: the server returns 402 Payment Required with a structured payment requirement, and a paying agent retries with proof of payment. This is the monetization thesis in one endpoint — *agents discover, agents pay*. The payment rail (x402/USDC or Stripe metered billing) is wired at deploy time.


Repository

rattlewatch/

rattlewatch/ store.py # ground-truth store (facts, recalls, events, sources) compile.py # ingest CPSC + cited rules engine.py # query logic (search, verify, change feed) textutil.py # normalization + matching primitives mcp_server.py # MCP server (stdio + streamable HTTP) api.py # FastAPI REST + x402 stub main.py # CLI: build / stats / serve / mcp data/rules/seed.yaml # cited facts tests/test_engine.py # correctness + no-hallucination tests

Why this matters

AI generates infinite plausible text for free, so content is worth nothing. But AI hallucinates — especially on current rules, specific numbers, and what changed last week. Rattlewatch is the opposite of a generative model: a small, boring, cited layer of truth that agents and the software they power can depend on when being wrong is expensive.

Security

See [SECURITY.md](SECURITY.md) for the full threat model, the implemented controls, and — listed explicitly — what is not protected. Every claim there is backed by a test in tests/test_api.py.

Highlights: query input bounded at two independent layers; per-client rate limiting; API keys compared in constant time that fail closed; CORS denied by default; hardened response headers; no stack-trace leakage; container runs as an unprivileged user (UID 10001).

Testing

export PYTHONPATH=.

python tests/test_engine.py # 13 checks — correctness + non-hallucination python tests/test_api.py # 30 checks — security + abuse

See [TESTING.md](TESTING.md) for the coverage map and an explicit list of what is *not* tested. A green run is not the same as "verified secure."

License

MIT — see LICENSE.

The code is open source; the hosted service is the product. Nothing about the moat lives in the source: the defensible asset is the curated, daily-refreshed, cited corpus and the freshness pipeline that maintains it. Open-sourcing the code also means the citation machinery is auditable — which matters for a product whose entire claim is that its answers can be trusted.

You can self-host it:

docker build -t rattlewatch .

docker run -p 8000:8000 rattlewatch

Or use the hosted endpoint: https://rattlewatch.rattled.ca

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