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)
AI-crawler readiness checks and fixes: GEO score, robots.txt, schema.org, FAQ and llms.txt.
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。
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": {
"geoscore": {
"command": "npx",
"args": [
"-y",
"@reneturcios/geoscore",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add geoscore -- npx -y @reneturcios/geoscore mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"geoscore": {
"command": "npx",
"args": [
"-y",
"@reneturcios/geoscore",
"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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"geoscore": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/geoscore",
"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。
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。
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6日
注册名称已通过 GitHub 账户 CloudCorpRecords 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。
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–,最新版本(0.1.0)于3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, Docker。
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。
Can ChatGPT, Claude and Perplexity actually see your site? geoscore checks a website's readiness for AI crawlers and search — its GEO (Generative Engine Optimization) — and hands back the fixes as copy-paste assets: a robots.txt that lets the named AI crawlers in, Schema.org Organization and FAQ markup, and an llms.txt. It runs locally over stdio, needs no account and no API key.
Five tools do the work. analyze_geo_score grades an existing domain from 0 to 100 with a per-category breakdown. get_geo_fixes renders the repair kit for that domain. make_site_geo_ready generates every asset for a brand-new site in one shot from a name, a URL and a description. suggest_monitoring_config drafts the monitoring setup for a business — target audiences, suggested queries, and the exact causabi.com API calls that would apply it. get_site_report returns a client-ready report: the full mention-rate breakdown when you have a causabi.com share slug, or the crawlability score on its own when you only have a domain.
src/geo.ts.causabi.com/report/ are public; the API path behind them (https://causabi.com/api/v1/reports/ ) is this rebuild's rendering of that behaviour.None. No environment variables, no API key. Site facts are fetched directly from the domain being checked, with a fixed 15-second per-request timeout.
analyze_geo_score — GEO score 0–100 plus a breakdown for an existing domain. The result is a JSON object: {domain, score, breakdown: {crawlability, robots, visibility, schema, faq, contacts, hygiene}, robots: { : "allowed" | "blocked"}, facts: {home_status, has_llms_txt, has_json_ld}}. The eight crawlers tracked are GPTBot, ClaudeBot, PerplexityBot, ChatGPT-User, Claude-User, OAI-SearchBot, Google-Extended and CCBot. If the home page cannot be fetched at all the tool fails with site unreachable: ; a reachable page with an HTTP error status is scored, not fatal.get_geo_fixes — the copy-paste fixes for a domain, as a markdown document with four sections: a robots.txt block allowing every named AI crawler (listing any the current robots.txt blocks), an Organization JSON-LD template filled with the site's title when discoverable, a FAQPage JSON-LD skeleton, and an llms.txt skeleton.make_site_geo_ready — all GEO assets for a new site in one shot (no API key needed). Takes name, url and description, plus optional services (array of strings), email, and faq (array of {question, answer}). Returns one document: Organization JSON-LD, a FAQPage JSON-LD block when faq is given, an llms.txt body (with a Services list when given), and a robots.txt allowing the named AI crawlers. Fully local — it never fetches.suggest_monitoring_config — draft a monitoring config from business_name and business_description, with an optional location. Returns JSON: {business_name, location, audiences, suggested_queries, apply_calls}, where apply_calls holds the two calls that apply the config on causabi.com — PUT https://causabi.com/api/v1/monitor/{site_id}/settings and PUT https://causabi.com/api/v1/monitor/{site_id}/queries — with the {site_id} placeholder. This tool itself makes no API call.get_site_report — pass report_slug for the full AI mention-rate breakdown (no API key needed), or just domain for a crawlability-score-only summary: the analyze_geo_score JSON plus a note field explaining how to get the full report. One of the two arguments is required.npx @reneturcios/geoscore analyze_geo_score '{"domain":"example.com"}'
npx @reneturcios/geoscore get_geo_fixes '{"domain":"example.com"}' npx @reneturcios/geoscore make_site_geo_ready '{"name":"Acme Corp","url":"https://acme.com","description":"We help small businesses grow."}' npx @reneturcios/geoscore suggest_monitoring_config '{"business_name":"Bright Smiles Dental","business_description":"A family dental clinic.","location":"Austin, TX"}' npx @reneturcios/geoscore get_site_report '{"report_slug":"abc123"}' npx @reneturcios/geoscore --version
Each subcommand takes one JSON argument string and prints the tool's result text. Exit codes: 0 success, 1 tool error, 2 usage error.
npx -y @reneturcios/geoscore mcp
MCP client config:
{
"mcpServers": { "geoscore": { "command": "npx", "args": ["-y", "@reneturcios/geoscore", "mcp"] } } }
docker run -i ghcr.io/cloudcorprecords/geoscore # stdio MCP server (CMD defaults to "mcp")
docker run --rm ghcr.io/cloudcorprecords/geoscore analyze_geo_score '{"domain":"example.com"}' # CLI via container
npm install
npm run build # tsc -> dist/ (dist/cli.js is the bin) npm test # tsx --test test/*.test.ts — fixture-based, no network npm run dev # tsx src/cli.ts — run the CLI from source
MIT — see LICENSE (Copyright (c) 2026 Rene Turcios).