Browser Use
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
제작자가 쓴 설명(영어 원문)
Check what AI crawlers may read and what a page permits, generate llms.txt and schema.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
CRAWL_READINESS_API_KEY, CRAWL_READINESS_API_BASE비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"crawl-readiness": {
"command": "npx",
"args": [
"-y",
"crawl-readiness-mcp"
],
"env": {
"CRAWL_READINESS_API_KEY": "your-value",
"CRAWL_READINESS_API_BASE": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add crawl-readiness --env CRAWL_READINESS_API_KEY=your-value --env CRAWL_READINESS_API_BASE=your-value -- npx -y crawl-readiness-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"crawl-readiness": {
"command": "npx",
"args": [
"-y",
"crawl-readiness-mcp"
],
"env": {
"CRAWL_READINESS_API_KEY": "your-value",
"CRAWL_READINESS_API_BASE": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"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"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
CRAWL_READINESS_API_BASE env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 Grubbomatic 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: CRAWL_READINESS_API_KEY
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.2.9)은 8일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Browser Use, Chrome DevTools MCP, MCP Server Browser
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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