Browser Use
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
作者提供的说明(英文原文)
Check what AI crawlers may read and what a page permits, generate llms.txt and schema.
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。
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。
CRAWL_READINESS_API_KEY, CRAWL_READINESS_API_BASE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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"crawl-readiness": {
"command": "npx",
"args": [
"-y",
"crawl-readiness-mcp"
],
"env": {
"CRAWL_READINESS_API_KEY": "your-value",
"CRAWL_READINESS_API_BASE": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add crawl-readiness --env CRAWL_READINESS_API_KEY=your-value --env CRAWL_READINESS_API_BASE=your-value -- npx -y crawl-readiness-mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"crawl-readiness": {
"command": "npx",
"args": [
"-y",
"crawl-readiness-mcp"
],
"env": {
"CRAWL_READINESS_API_KEY": "your-value",
"CRAWL_READINESS_API_BASE": "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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"crawl-readiness": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"crawl-readiness-mcp"
],
"env": {
"CRAWL_READINESS_API_KEY": "your-value",
"CRAWL_READINESS_API_BASE": "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。
CRAWL_READINESS_API_BASE 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。
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7日
注册名称已通过 GitHub 账户 Grubbomatic 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
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
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 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。
你需要填写:CRAWL_READINESS_API_KEY
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–,最新版本(0.2.9)于8天前进入注册中心。
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:Browser Use, Chrome DevTools MCP, MCP Server Browser
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
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
MCP server for Chrome DevTools
MCP server for browser use access
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。
An MCP server that checks whether a website is set up for AI the way its owner intends: can GPTBot, ClaudeBot, PerplexityBot and 50+ other AI crawlers read it, and what does its access policy allow? Then it generates the files (llms.txt, an AI-crawler robots.txt, JSON-LD structured data), reads your Answer Analysis, and tells you whether a page's published signals permit a use (search, answers, training, agent action), inside Claude Desktop, Cursor, Cline, Windsurf and other MCP clients.
Ask Claude "can AI read my site?" and it will actually check, running a live audit against 50+ AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google's and more) and reading the access policy the site states. Then ask it to fix what is blocked, and it can generate a proper llms.txt, robots.txt or JSON-LD schema and write it straight into your project.
No more copy-paste between your editor and a browser.
Nine tools your AI assistant can call:
Audit (no signup):
check_ai_readiness — Score a site 0–100 against 50+ AI crawlers, with a prioritized fix list; extras that don't affect the score are marked as suchvalidate_schema — Audit JSON-LD structured data on any URL (20+ types, per-type rules)validate_robots — Line-by-line robots.txt auditcheck_content_parity — Compare what humans see vs what AI crawlers seePermission (no signup):
check_permission — Ask whether a page may be used for search, answers, training or agent action. Reads robots.txt, Content-Signal, Content-Usage, an RSL licence, the TDM reservation, ai.txt and the page's own directives: any reservation wins, and a source that could not be read makes the answer unknown, never allowed. Returns a dated receipt signed with Ed25519, with a hash of every file read. Documented at machinereadiness.com/permissionGenerate (requires free API key):
generate_llms_txt — Auto-crawl a site and produce a properly formatted llms.txtgenerate_robots_txt — AI-crawler-aware robots.txt with preset policiesgenerate_schema — Organization / WebSite / Article JSON-LD ready to pasteAnswer Analysis (read-only; needs an API key, and the analyses come with Monitor, Agency or the audit):
get_monitor_trend — Read your Answer Analysis: for the questions your customers ask, whether live AI search (Perplexity, Google AI Overviews) named your brand or a competitor, and the change run over run (reads existing analyses; doesn't trigger runs)Download crawl-readiness-mcp- .mcpb from the latest release and double-click it (or drag it into the Claude Desktop window). Claude Desktop shows what the extension does and asks for the optional API key. The bundle carries the server and its dependencies, so nothing else is installed.
This repository is also a Claude plugin: the .mcp.json at its root starts the server (pinned to this version), and the ai-readiness skill tells Claude when to use which tool and how to read the results. Add it from the Claude directory once it is listed there. To try it before then, clone the repository and start Claude Code with it loaded:
claude --plugin-dir ./crawl-readiness-mcp
Claude Code asks for the optional API key when the plugin is enabled and keeps it in secure storage; the plugin's own files never contain it.
Open your config file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonAdd this to the mcpServers block:
{
"mcpServers": { "crawl-readiness": { "command": "npx", "args": ["-y", "crawl-readiness-mcp"] } } }
Restart Claude Desktop. You'll see "crawl-readiness" listed in the tools panel.
Open Cursor Settings → Features → Model Context Protocol → Add new global MCP server.
{
"crawl-readiness": { "command": "npx", "args": ["-y", "crawl-readiness-mcp"] } }
Same shape — add crawl-readiness to your MCP servers list with npx -y crawl-readiness-mcp as the command.
The five checks (the four audit tools and check_permission) work out of the box, no signup. The three generator tools need an API key — free at crawlreadiness.com/dashboard (50 checks/month on the free tier, no credit card). get_monitor_trend needs a key too, on a plan that includes Answer Analyses (Monitor, Agency or the audit).
Once you have a key, add it via env in the same config:
{
"mcpServers": { "crawl-readiness": { "command": "npx", "args": ["-y", "crawl-readiness-mcp"], "env": { "CRAWL_READINESS_API_KEY": "cr_live_xxxxxxxxxxxx" } } } }
Restart the client. All nine tools are now callable.
Once installed, try any of these in your AI client:
/public/llms.txt"*Your AI can chain tools automatically — audit, identify issues, fix them, and write files to your project without you copy-pasting anything.
| Env var | Purpose | Default |
|---|---|---|
CRAWL_READINESS_API_KEY | API key (free) for the generators; lifts the daily limit on check_permission; reads your Answer Analyses on a plan that includes them | none |
CRAWL_READINESS_API_BASE | Override the API base URL for every tool, the permission check included (for testing) | https://www.crawlreadiness.com |
Each tool returns the full JSON response from the Crawl Readiness API — the same data the web dashboard renders. Your AI has access to:
extra: true are optional and not scored)denied, allowed-under-terms, allowed, unknown) with the reason, every signal as it was read, the page's status, and the signed receipt with a hash of every file read; with observe: true, also how the server treated a crawler's user-agent string sent from our serversEvery tool makes HTTPS requests to https://www.crawlreadiness.com, and check_permission to https://machinereadiness.com (the same service on the standard's own host), and nowhere else. What leaves your machine is the website address (and for the generators, the inputs) you asked about, the API key if you configured one, and a crawl-readiness-mcp/ user agent. The server stores nothing locally, runs no other programs, and reads no files; writing a generated file into your project is something your AI client does, with your say-so. The service's own data handling is described at crawlreadiness.com/privacy.
The plugin's .mcp.json starts the published npm package pinned to the same version as the repository (npx -y crawl-readiness-mcp@ ), so what runs is the code in this repository at that tag.
Crawl Readiness checks whether a website is set up for AI the way its owner intends: what AI crawlers can read, what its access policy allows, and what is missing, with the files that fix it. Every generator tool in this MCP server is also available on the web at crawlreadiness.com/tools. The MCP server just makes the same tools callable from inside your AI assistant, so the "audit → fix → apply" loop happens in one conversation without leaving your editor.
npm run release validates server.json and prints the publish steps. The last step uses the mcp-publisher CLI, which is not part of this repository: download it from the MCP Registry releases and keep it on your PATH or in the repo root (it is git-ignored there).
MIT © 2026 Crawl Readiness / Tundrastone