World Monitor
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.
作者提供的说明(英文原文)
Free App Store competitive intelligence for Claude — rival downloads, revenue, and ASO keywords.
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。
选择你使用的 AI 应用,然后复制设置。
通过 2/2 项检查 · 在你的电脑上运行
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
需要 App Store Operator 的密钥(在开发者网站注册,可能收费) · 需要先在电脑上安装 Node.js(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
SettingsDeveloperEdit Config
{
"mcpServers": {
"app-store-operator": {
"command": "npx",
"args": [
"-y",
"app-store-operator"
],
"env": {
"ASO_CACHE_TTL_HOURS": "your-value"
}
}
}
}只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
用 App Store Operator 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 App Store Operator,或回答中出现 App Store Operator 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 App Store Operator
App Store Operator 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
A · 使用能连接 App Store Operator 的应用
B · 其他 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
可连接 Claude Code,但需要先准备
需要 App Store Operator 的密钥(在开发者网站注册,可能收费) · 需要先在电脑上安装 Node.js(只需一次)
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
claude mcp add app-store-operator --env ASO_CACHE_TTL_HOURS=your-value -- npx -y app-store-operator按 Enter 前,把“your-value”改成你的密钥
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
应能看到 App Store Operator 在列表中并显示已连接
用 App Store Operator 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 App Store Operator,或回答中出现 App Store Operator 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor,但需要先准备
需要 App Store Operator 的密钥(在开发者网站注册,可能收费) · 需要先在电脑上安装 Node.js(只需一次)
在 App Store Operator 的设置中,ASO_CACHE_TTL_HOURS 还是空的,填入你的密钥并保存
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
用 App Store Operator 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 App Store Operator,或回答中出现 App Store Operator 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code,但需要先准备
需要 App Store Operator 的密钥(在开发者网站注册,可能收费) · 需要先在电脑上安装 Node.js(只需一次)
在 App Store Operator 的设置中,ASO_CACHE_TTL_HOURS 还是空的,填入你的密钥并保存
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
用 App Store Operator 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 App Store Operator,或回答中出现 App Store Operator 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
Claude Code
claude mcp add app-store-operator --env ASO_CACHE_TTL_HOURS=your-value -- npx -y app-store-operatorClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"app-store-operator": {
"command": "npx",
"args": [
"-y",
"app-store-operator"
],
"env": {
"ASO_CACHE_TTL_HOURS": "your-value"
}
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"app-store-operator": {
"command": "npx",
"args": [
"-y",
"app-store-operator"
],
"env": {
"ASO_CACHE_TTL_HOURS": "your-value"
}
}
}
}VS Code (mcp.json)
{
"servers": {
"app-store-operator": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"app-store-operator"
],
"env": {
"ASO_CACHE_TTL_HOURS": "your-value"
}
}
}
}ASO_CACHE_TTL_HOURS env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。
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
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。
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11日
注册名称已通过 GitHub 账户 meyusufdemirci 验证,该账户拥有此仓库
代码最后更新于2个月前
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
还没有评价
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。
它在 2 项适用的基础检查中通过了 2 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。
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)。
GitHub 仓库最后更新于2个月前,最新版本(0.3.5)于3个月前进入注册中心。
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 Node.js。
同一分类中有:World Monitor, Claude Flow, Tldraw
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
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。
App Store competitive intelligence, inside Claude.
App Store Operator is an MCP server that brings App Store research directly into your AI assistant. Instead of switching to a dashboard, you ask Claude for ranked keyword results, competitor download and revenue estimates, or App Store Connect-ready In-App Event copy — and get the answer in the same conversation where you are making the decision.
Built for indie iOS developers who want research inside their workflow rather than in another browser tab. Free and open source (MIT). A lightweight alternative to SensorTower, AppTweak, and AppFollow for iOS-only competitive research.
claude mcp add --transport stdio app-store-operator -- npx -y app-store-operator@latest
→ app-store-operator.com · Setup guide
Searches the App Store for competing apps on a given keyword and pulls detailed analytics from SensorTower — downloads, revenue, ratings, top markets, publisher info, and more.
search_app_store and prepare_iae work with no account at all. research_rivals and get_app_details open a browser once for a free SensorTower sign-in, then reuse that saved session — no paid plan, no API key.
Everything the server exposes — four tools, six prompts, seven resources — is read-only. Nothing writes to your App Store Connect account, to SensorTower, or anywhere but a local cache file.
research_rivalsFinds the top 3 apps for a keyword and returns a full metrics report for each.
| Parameter | Type | Description |
|---|---|---|
keyword | string | Search term to look up (e.g. meditation, psikoloji) |
country | string | Two-letter country code (e.g. us, tr, gb) |
Returns for each competitor:
Cached for 24 hours, so asking again about the same keyword and country costs nothing and opens no browser.
search_app_storeSearches the App Store for a keyword and returns ranked results as a markdown table — instantly, no SensorTower required.
| Parameter | Type | Description |
|---|---|---|
keyword | string | Search term to look up |
country | string | Two-letter country code |
limit | number | Number of results to return (1–25, default 3) |
Use this to discover which apps rank before deciding which to analyse. Follow up with get_app_details for analytics on specific apps.
get_app_detailsFetches SensorTower analytics for one or more app IDs you already have.
| Parameter | Type | Description |
|---|---|---|
app_ids | array | Numeric App Store IDs (e.g. from search_app_store) |
country | string | Two-letter country code |
Returns for each app:
Never cached — every call scrapes fresh, at roughly 10–20 seconds per app ID.
prepare_iaeGenerates iOS App Store In-App Event (IAE) copy — 3 variations in the target language, then a final report.
| Parameter | Type | Description |
|---|---|---|
keywords | array | Ordered keywords by priority (index 0–2 = Tier 1, 3–6 = Tier 2, 7–9 = Tier 3) |
locale | string | Target locale (e.g. en-us, en-gb, de-de, tr, ja, ko) |
event_purpose | string | What the event is about and why users should care |
audience | string | Target audience (e.g. students, professionals, parents) |
event_context | string | Real-world hook tying the event to a moment (e.g. a holiday, season) |
goal | string | Primary conversion goal (e.g. attract new users, boost engagement) |
tone | string | Copy tone: Engaging, Playful, Motivational, Authoritative, Calm, or Urgent |
Returns: a structured brief used to generate 3 copy variations, each with event name (≤30 chars), short description (≤50 chars), and long description (≤120 chars).
Any field SensorTower does not expose, or keeps behind its paywall, comes back as N/A. The server reports the gap rather than filling it, and the prompts below tell the assistant to do the same.
Six ready-made workflows that already chain the tools above, so you don't have to describe the sequence yourself. In Claude Code they appear as slash commands; other clients surface them in a prompt picker.
| Prompt | Arguments | What it does |
|---|---|---|
competitor_snapshot | keyword, country | Pulls rival analytics for a keyword, then reads out who owns it and how contested it is |
keyword_shortlist | seed_keyword, country, count? | Expands a seed keyword into candidates, tests each against live search results, and ranks them *attack / watch / skip* |
app_teardown | app_ids, country | Teardown of known apps — scale, standing, monetisation, reach, momentum, acquisition |
positioning_gap | keyword, country, my_app_id | Puts your app on the same measuring stick as the incumbents and separates *behind* from *attackable* |
metadata_rewrite | app_name, keyword, country, must_keep? | Three name / subtitle / keyword-field variations, character-counted against Apple's limits |
in_app_event | event_context, locale, keywords?, audience?, tone? | Runs the full In-App Event flow, asking for whatever prepare_iae still needs |
Arguments marked ? are optional. Every prompt tells the assistant not to invent figures and, where SensorTower is involved, not to quietly fall back to a weaker tool when login is required.
Reference data and local state a client can attach as context without spending a tool call on it.
| URI | Type | Contents |
|---|---|---|
asops://guide/tool-selection | markdown | Which tool to use, what each costs, how the SensorTower login works |
asops://reference/country-codes | markdown | Two-letter storefront codes by region |
asops://reference/aso-fields | JSON | App Store Connect character limits and which fields are indexed for search |
asops://reference/iae-fields | JSON | In-App Event limits, artwork sizes, copy rules, keyword tiers |
asops://reference/iae-locales | JSON | Every locale prepare_iae accepts — generated from the same table the tool validates against |
asops://cache/research | JSON | What has already been researched on this machine, and whether it is still fresh |
asops://cache/research/{country}/{keyword} | JSON | One cached research_rivals result, without re-scraping |
Nothing here leaves your machine: the reference resources are static, and the two cache resources read ~/.app-store-operator/cache.json.
research_rivals and get_app_details. They drive a real, visible Chromium window so you can sign in to SensorTower, so they need a display — they do not work over plain SSH or inside a container. The other two tools have no such requirement.npx playwright install chromium yourself.Claude Code — run this command once:
claude mcp add --transport stdio app-store-operator -- npx -y app-store-operator@latest
Claude Desktop — add to your MCP config:
{
"mcpServers": { "app-store-operator": { "command": "npx", "args": ["app-store-operator@latest"] } } }
OpenAI Codex — run this command once:
codex mcp add app-store-operator -- npx -y app-store-operator@latest
Codex stores MCP servers in ~/.codex/config.toml. If you prefer to edit it directly:
[mcp_servers.app-store-operator]
command = "npx" args = ["-y", "app-store-operator@latest"]
startup_timeout_sec = 20 tool_timeout_sec = 180
Then restart Codex or start a new thread, and ask things like:
Research rivals for "hairstyle" in the GB App StoreSearch the App Store for "beard style" in FrancePrepare an in-app event for a summer hairstyle campaign in en-gbNo installation step needed — npx fetches and runs the package automatically.
The server communicates over stdio and is designed to be invoked by an MCP client. It advertises server-wide instructions during initialize so clients route between the tools correctly, and returns an MCP tool error when SensorTower login is required.
Both settings are optional environment variables on the server process.
| Variable | Default | What it does |
|---|---|---|
ASO_CACHE_TTL_HOURS | 24 | How long a research_rivals result stays fresh in the local cache before it is scraped again |
ASO_DEBUG_RATINGS | unset | Set to 1 to print SensorTower's ratings panel to stderr when a rating score or count comes back N/A — useful when reporting a scraping bug |
The repo ships a Dockerfile built on Playwright's official image:
docker build -t app-store-operator .
docker run -i --rm app-store-operator
The server speaks JSON-RPC over stdio, so no port is exposed — point your MCP client at the container's stdin/stdout. Note that a container has no display: search_app_store and prepare_iae work there, but the two SensorTower tools cannot open a login window and will fail rather than prompting you to sign in.
SensorTower data is scraped via Playwright because it is rendered client-side.
A browser window will open. This is deliberate, not a bug: SensorTower requires a login, so the first run opens a visible window for you to sign in. The session is saved to ~/.app-store-operator/profile and reused on every later call, so you only log in once. If a tool reports not_logged_in, finish signing in on that window and run the tool again.
Results from research_rivals are cached for 24 hours in ~/.app-store-operator/cache.json — override the TTL with the ASO_CACHE_TTL_HOURS environment variable.
research_rivals is fixed at the top 3 resul