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

Shop MCP

作者:hello532版本 1.0.1i★ –i在你的电脑上运行
注册名称io.github.hello532/shop-mcp

安装

概览

作者提供的说明(英文原文)

Read-only Shopify catalogue and stock for LLM agents. Stdlib only, no dependencies.

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: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 网店与支付
  • 你需要填写:SHOPIFY_SHOP_DOMAIN, SHOPIFY_ADMIN_TOKEN

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: SHOPIFY_SHOP_DOMAIN, SHOPIFY_ADMIN_TOKEN

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

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

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 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "shop": {
      "command": "uvx",
      "args": [
        "shop-mcp"
      ],
      "env": {
        "SHOPIFY_SHOP_DOMAIN": "your-value",
        "SHOPIFY_ADMIN_TOKEN": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add shop --env SHOPIFY_SHOP_DOMAIN=your-value --env SHOPIFY_ADMIN_TOKEN=your-value -- uvx shop-mcp

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": {
    "shop": {
      "command": "uvx",
      "args": [
        "shop-mcp"
      ],
      "env": {
        "SHOPIFY_SHOP_DOMAIN": "your-value",
        "SHOPIFY_ADMIN_TOKEN": "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": {
    "shop": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "shop-mcp"
      ],
      "env": {
        "SHOPIFY_SHOP_DOMAIN": "your-value",
        "SHOPIFY_ADMIN_TOKEN": "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。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

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

  • SHOPIFY_SHOP_DOMAIN 必填 env
    Your store domain, e.g. your-shop.myshopify.com
  • SHOPIFY_ADMIN_TOKEN 机密 必填 env
    Shopify Admin API access token (shpat_...) with read_products and read_inventory scopes

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

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

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 hello532 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

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“网店与支付”中的其他服务器比较i

  • 星标数多于此分类中其他 1759 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1759 个服务器的 37% 更新
  • 基础检查结果等于或优于此分类中其他 1759 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

Shop MCP 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?

你需要填写:SHOPIFY_SHOP_DOMAIN, SHOPIFY_ADMIN_TOKEN

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.0.1)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。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spree Commerce: open-source B2B and marketplace ecommerce, Stripe MCP, MCP Cn Commerce

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

Stripe MCP

作者:stripe

MCP server integrating with Stripe - tools for customers, products, payments, and more.

在云端运行★ 2,043MIT12个月前更新
安装

MCP Cn Commerce

作者:TonyWang-hub

8 read-only MCP platform entries; support is operation-specific; merchant live acceptance pending

在你的电脑上运行★ 96MIT28天前更新
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。

shop-mcp

A Model Context Protocol server that lets an LLM agent answer questions about a Shopify store's catalogue and stock — over stdio, from a single file, using only the Python standard library.

No MCP SDK. No requests. No GraphQL client. python3 shop_mcp.py is the whole install.

$ python3 shop_mcp.py --self-test

all green: 200 assertions

That command needs no credentials and no network. It is the point of the repo: the protocol layer and the tool layer are both exercised for real, because the Shopify transport is replaced at a seam rather than mocked at the boundary.

Installed from PyPI, the same command reports 183, and the seventeen-assertion difference is a packaging fact rather than a weaker check:

$ uvx --from shop-mcp shop-mcp --self-test

all green: 183 assertions

manifest.json (5 assertions), llms-install.md (11) and README.md (1) are deliberately not shipped into site-packages — the manifest's entry_point names a bundle path that does not exist in an installed copy, so packaging it would make a correct install fail. All three groups *skip* rather than fail when their file is absent, which is why the count moves and the verdict does not. Clone the repo to run all 200.

This server is the worked example, not a product line. I build the same shape — a stdio MCP server over data you already have, with a self-test suite and proof that the suite catches injected defects — as a fixed-price job: hello532.github.io/services.html, or coolun.337@gmail.com. Nothing on this page needs paying for; issues and PRs are welcome either way.

Why write the protocol by hand

Because the failure modes of a stdio MCP server are all invisible locally and all fatal in a host. Each one below is a real defect this file is built to not have, and each has an assertion naming it:

  • A diagnostic on stdout. One stray print() corrupts the client's next parse. Nothing looks wrong when you run the server yourself. Every diagnostic here goes to stderr, and a test asserts stdout stays byte-empty across a full session.
  • Answering a notification. notifications/initialized has no id, so a reply to it is a message with no pending request. Strict clients treat that as a protocol violation and drop the connection.
  • `id: 0` read as a notification. if msg.get("id") is falsy for zero, so a client that numbers requests from zero has its first call silently dropped. Presence, not truthiness.
  • Tool failures sent as JSON-RPC errors. A JSON-RPC error is for a malformed *request*. A tool that ran and failed must return a normal result with isError: true and the reason as text — otherwise the model never sees the message and cannot correct its own arguments.
  • Echoing an unknown `protocolVersion`. If a client asks for a revision the server does not know, agreeing to it leaves both sides believing a spec is in use that neither implements. This falls back to 2025-03-26, the spec's own default, and says so.
  • Pretty-printing the reply. Indented JSON contains newlines, and newline is the frame delimiter. One message becomes several broken ones.

Tools

toolanswers
search_products"what do we sell that matches X" — identity and total stock
get_productone product in full, every variant with SKU, price, stock
check_inventorystock for a SKU per location: available, committed, on-hand
low_stock_reportvariants at or below a threshold, lowest first

Four tools, chosen because each answers a question a shop owner actually asks. A wider surface would be easy and would make the model worse at picking.

The correctness that is not protocol

Three of the assertions cover mistakes that produce *confidently wrong answers*, which are worse than errors:

  • An unquoted SKU. sku:SH 1 is a different query from sku:"SH 1". The first silently matches the wrong variants and reports their stock as if it were yours. SKUs are quoted and internal quotes escaped.
  • A null quantity read as zero. Shopify returns null for a variant that does not track inventory. Coerced to 0, it appears in every restock report forever. Untracked and out-of-stock are different facts and stay different.
  • `scan_exhausted`. low_stock_report scans a bounded number of variants. If the scan hit its limit, "nothing is low" is indistinguishable from "I did not look far enough" — so the result says which it was, and the model can say so too.

Plus the transport rules any Shopify client needs and most skip: a THROTTLED GraphQL response is a *200* and must be retried, not read as success; a 401 must *not* be retried, because waiting will not fix a bad token; backoff must actually grow.

Verified, and not verified

Verified, by the self-test, on every run: 200 assertions covering the handshake, framing, notification handling, id presence, error mapping, schema strictness, retry and backoff policy, SKU quoting, null-quantity handling, threshold boundaries, and scan exhaustion. Wire shapes were taken from the official mcp Python SDK's types.py (LATEST_PROTOCOL_VERSION, CallToolResult, ServerCapabilities), not from memory.

Not verified: this has never been run against a live Shopify store. There is no credential in this repo and no recorded API session. The Shopify Admin GraphQL queries are written to the documented schema, and every code path around them is tested against a transport double — but the round trip against a real shop is unproven, and the test doubles are my model of Shopify's behaviour, not Shopify.

That distinction is the honest one, and it is the same line drawn in gpt-ads-feed. A README that blurs it is asking to be trusted on the wrong thing.

Assertions that can fail

mutation_test.sh injects known defects into *copies* of the source and asserts --self-test goes red for each, naming which assertion caught it. It also flags a NO-OP EDIT when a search pattern has gone stale — because a mutation that does not apply tests nothing while looking green, which is the failure mode that makes a suite worse than useless: trusted and empty.

It found real weaknesses in the suite on its first run, and all three were the same shape: the defect *was* detected, but by an exception rather than by a named assertion, so the message explained nothing and every assertion after it never ran.

Two were an unhandled KeyError: 'result', from indexing a reply that the defect had turned into a JSON-RPC error. Fixed by routing result access through a shape guard, so the same defect now reports a tool crash returns a result, so the loop survives: reply is a JSON-RPC error {'code': -32603, ...} and the three following assertions each still report their own verdict.

The third was a bare setup call — S.Tools(c).search_products(...), present only to make the assertion below it meaningful. When the throttle branch was disabled it raised, aborting the test before that assertion ran. Fixed with completes(), the exact inverse of raises(): the defect now reports a 200-with-THROTTLED is survivable, not a hard failure: raised ShopifyError: Throttled [THROTTLED], naming the rule and keeping the cause.

Three more defects surfaced only when the server was packaged as an .mcpb bundle and launched the way a host launches it, which no test had ever done:

  1. The code read SHOPIFY_SHOP; this README and the bundle manifest both told users to export SHOPIFY_SHOP_DOMAIN. Anyone following the docs got a permanently unconfigured server. Every one of the 180 assertions passed, because none of them compared the code against the docs.
  2. tools/list returned [] until credentials existed, so a host saw an empty server and reported it broken — and the readable *no store is configured* message on tools/call was unreachable, since nothing was listed to call. The docstring above that code stated the opposite requirement, and the test below it asserted the defect: eq(tools, [], ...). The list never depended on credentials; descriptors() touched no instance state at all, and is now a staticmethod.
  3. --self-test was advertised in the module docstring but crashed inside the bundle, which shipped only the server file. The bundle now ships the suite.

The first fix then broke the harness in a way worth recording. The new assertion failed when README.md was absent, and the harness copied only two files, so it fired inside *every* mutant. The run still printed 17 caught, but six of those were credited to README.md is present instead of their own labels: six real assertions could have been dead with the suite still green. A missing README is a packaging fact, not a code defect. The load-bearing comparison now runs against the module docstring, which travels with the source, and the harness copies the README so the cross-check is real.

All 23 mutations are caught by an assertion that names what broke, and each is credited to its own label.

Use it

Installed from PyPI — nothing to clone:

export SHOPIFY_SHOP_DOMAIN=your-shop.myshopify.com

export SHOPIFY_ADMIN_TOKEN=shpat_... # read_products, read_inventory uvx shop-mcp # or: pip install shop-mcp && shop-mcp

Claude Desktop / any MCP host:

{

"mcpServers": { "shop": { "command": "uvx", "args": ["shop-mcp"], "env": { "SHOPIFY_SHOP_DOMAIN": "your-shop.myshopify.com", "SHOPIFY_ADMIN_TOKEN": "shpat_..." } } } }

From a clone instead, when you want to read the source before running it — which is the point of a single dependency-free file, and the only way to get the full 200-assertion suite:

python3 shop_mcp.py --self-test    # 200 here, 183 installed; see above

python3 shop_mcp.py

{ "command": "python3", "args": ["/absolute/path/to/shop_mcp.py"] }

With no credentials set it still completes a handshake and serves tools/list, then returns isError with the missing variable named. A host that cannot read tools/list reports "broken server" and sends you looking in the wrong place.

MIT.

问 PopNx