Web Metadata, OpenGraph & Contact Extractor

Name: Web Metadata, OpenGraph & Contact Extractor
Author: JosejuX

作者：JosejuX版本 1.0.0i★ –i在云端运行

注册名称io.github.JosejuX/rapidapi-metadata-extractor

安装

概览

作者提供的说明（英文原文）

Turns any URL into SEO metadata, contacts, tech stack, and AI-ready Markdown, in one call.

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。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

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: 在云端运行
传输方式: Streamable HTTP
分类: 营销与社交媒体
你需要填写：x-api-host, x-api-key

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
在作者的服务器上运行：你向它提出的内容会经过他们的服务器。
需要你自己填写： x-api-host, x-api-key

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

在云端运行无需安装任何东西，通过互联网连接

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

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 …”。

这个地址需要在请求的 header 中放入密钥，而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。

在终端中运行这条命令

claude mcp add --transport http rapidapi-metadata-extractor https://mcp.rapidapi.com --header 'x-api-host: your-value' --header 'x-api-key: your-value'

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": {
    "rapidapi-metadata-extractor": {
      "url": "https://mcp.rapidapi.com",
      "headers": {
        "x-api-host": "your-value",
        "x-api-key": "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": {
    "rapidapi-metadata-extractor": {
      "type": "http",
      "url": "https://mcp.rapidapi.com",
      "headers": {
        "x-api-host": "your-value",
        "x-api-key": "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。

这个地址需要在请求的 header 中放入密钥，而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。

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

x-api-host 必填 HTTP header
RapidAPI host header - use exactly: web-metadata-and-contact-extractor.p.rapidapi.com
x-api-key 机密必填 HTTP header
Your RapidAPI key - get a free one at https://rapidapi.com/josejuanjocoding/api/web-metadata-and-contact-extractor

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

我们还没有读取这个服务器的工具列表；我们会轮流检查各个端点。

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 JosejuX 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
… 尚未检查
端点有响应
尚未检查；我们会轮流检查各个端点
… 尚未检查
使用 OAuth 登录
尚未检查；我们会轮流检查各个端点
… 尚未检查
工具描述中没有隐藏指令
尚未检查；我们会在检查端点时读取工具列表

与“营销与社交媒体”中的其他服务器比较i

星标数多于此分类中其他 3569 个服务器的 0%
发布到注册中心的时间比此分类中其他 3569 个服务器的 24% 更新
基础检查结果等于或优于此分类中其他 3569 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

Web Metadata, OpenGraph & Contact Extractor 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：x-api-host, x-api-key

它在我的电脑上运行还是在云端？

它在作者的云端运行。通过互联网连接，无需安装，但你发送的内容会经过作者的服务器。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（1.0.0）于3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。它通过 URL 连接，所以接受远程 MCP 服务器的应用也可以使用，例如开启开发者模式的 ChatGPT。

有什么可以替代它？

同一分类中有：MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

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

MCP YouTube Transcript

作者：jkawamoto

An MCP server retrieving transcripts of YouTube videos

在你的电脑上运行★ 495MIT10天前更新

安装

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作者：surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

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BibiGPT YouTube Video Summarizer

作者：JimmyLv

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

在云端运行★ 137MIT11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。

Turn any URL into structured intelligence.

Extract SEO, technologies, contacts, products, social profiles, security signals, and AI-ready content from any public website — with one API call.

Free to try. No signup required for the demo.

🎮 Try the Live Demo • 🔑 Get Free API Key on RapidAPI • 📖 API Documentation • ⚡ Code Examples

Paste a URL, get real results in seconds — webmetadataextractor.com runs the actual pipeline live, no API key needed. Try your own site, or one of these:

/demo/extract is the same no-key route the live demo page above uses (see "Honest Limitations" — it's rate-limited per IP, not a documented/stable API endpoint). For integrating in code, use /api/v1/extract with a RapidAPI key as shown below.

Or call it directly (swap in your key from RapidAPI for production use):

curl "https://web-metadata-and-contact-extractor.p.rapidapi.com/api/v1/extract?url=github.com" \

-H "X-RapidAPI-Key: YOUR_KEY" -H "X-RapidAPI-Host: web-metadata-and-contact-extractor.p.rapidapi.com"

🎯 Use Cases

	Use case	What you get
🧲	Lead generation	Find companies on a given tech stack (e.g. Shopify) with a weak SEO score, then prioritize outreach.
🤖	AI agents	Feed `markdown_content` and structured JSON straight into an agent or RAG pipeline as clean, LLM-ready context for any URL.
🔎	SEO audits	Run the 14-point on-page score plus graded security headers across a URL list, on a schedule.
🛒	Ecommerce	Pull product name/price/currency/availability/brand from Schema.org, OpenGraph, and Microdata — cross-checked for conflicts.
🕵️	Competitive intelligence	Track a competitor's tech stack, metadata, and product data over time by re-checking the same URL list.

Example: lead generation — flag Shopify sites with a weak SEO score

import requests

RAPIDAPI_KEY = "YOUR_RAPIDAPI_KEY" HEADERS = { "X-RapidAPI-Key": RAPIDAPI_KEY, "X-RapidAPI-Host": "web-metadata-and-contact-extractor.p.rapidapi.com", } BASE = "https://web-metadata-and-contact-extractor.p.rapidapi.com/api/v1/extract"

for url in ["shop-a.com", "shop-b.com", "shop-c.com"]: data = requests.get(BASE, headers=HEADERS, params={"url": url}).json() if "Shopify" in data["detected_technologies"] and data["seo_score_percentage"] < 60: print(f"{url}: Shopify + {data['seo_score_percentage']}% SEO -> outreach candidate")

</details>

Example: AI agent tool call — clean Markdown for any URL

import requests

def read_url_as_markdown(url: str) -> str: """Tool function an LLM agent can call to read any public webpage.""" resp = requests.get( "https://web-metadata-and-contact-extractor.p.rapidapi.com/api/v1/markdown", headers={"X-RapidAPI-Key": "YOUR_KEY", "X-RapidAPI-Host": "web-metadata-and-contact-extractor.p.rapidapi.com"}, params={"url": url}, ).json() return resp["markdown_content"]

</details>

🌟 Key Features

Feature	Detail
⚡ Ultra-Fast Performance	~150–300ms live fetch. Powered by `selectolax` (C-Lexbor parser), Rust `ORJSON`, `uvloop`, HTTP/2 multiplexing, async DNS (non-blocking), 5-min DNS TTL cache.
🧠 Adaptive SPA Byte Limit	Auto-detects React, Next.js, Vue, Angular, Nuxt, Svelte, Gatsby, Remix, Astro and expands download to 256 KB for richer data extraction. Static sites stay at 64 KB.
🛡️ IP-Pinned Anti-SSRF Shield	DNS resolved once, IP validated against private/loopback/cloud-metadata ranges, connection pinned to IP with TLS SNI. Eliminates DNS Rebinding & Redirect SSRF.
🎯 Rich SEO & OpenGraph Metadata	Title, Description, OG Image, OG Type, OG URL, OG Video, Favicon, Canonical URL, Language, Author, Theme Color, Robots directive, hreflang tags, H1 headings, image count.
📧 Contact Extractor	Public emails and phone numbers with smart DOM cleaning to eliminate false positives. Phones are additionally normalized (`phone_details`) via libphonenumber — E.164 format, ISO country code, and possible/valid flags — for numbers that include a country code; numbers without one aren't guessed.
📲 Social Profile Finder	Auto-detects 20 platforms: Twitter/X, LinkedIn, Facebook, Instagram, GitHub, YouTube, Telegram, TikTok, Threads, Bluesky, Mastodon, Discord, Reddit, Pinterest, Medium, GitLab, Vimeo, Dribbble, Behance, Snapchat.
🛠️ 40+ Tech Stack Detector	WordPress, Shopify, WooCommerce, Webflow, React, Next.js, Vue, Angular, Svelte, TailwindCSS, Stripe, GA4, and more across CMS/ecommerce, frameworks, and analytics/payment/hosting categories.
📦 Schema.org JSON-LD + Product Parser	Parses all structured data schemas AND auto-extracts Product price, currency, availability, brand, rating and review count.
🎯 Multi-Source Data Quality & Conflict Detection	Product price/currency/availability/brand are cross-checked across three distinct structured encodings — JSON-LD, OpenGraph's product extension, and schema.org Microdata. `product_field_confidence` reports a per-field confidence score (more of these encodings agreeing = higher confidence, same philosophy as tech-stack detection) and which source won. When they genuinely disagree, a `SOURCE_CONFLICT` warning names the field, every value found, and which one was chosen and why. A top-level `quality` object (`score`, `rendered: false`, `sources_used`, `warnings`) summarizes response trustworthiness for programmatic consumers. Caveat: these three encodings often come from the same underlying product record on a given site, so agreement means "internally consistent," not "independently verified" — see Honest Limitations below.
📊 On-Page SEO Health Audit Score	14-point automated on-page technical SEO diagnostic (0–100%) with actionable warnings list, plus a structured `seo_checks` breakdown (`check` id, `passed`, `severity`, `evidence`) for programmatic use.
🔗 Internal vs External Link Classifier	Categorizes up to 100 hyperlinks per page.
🤖 AI & LLM Clean Markdown Reader	Converts article text to clean Markdown for ChatGPT, Claude, RAG, and AI agents. Includes word count and reading time.
📡 RSS / Atom Feed Discovery	Auto-discovers RSS and Atom feed URLs.
🔒 Graded Security Headers Audit	HSTS, CSP, X-Frame-Options, X-Content-Type-Options, Referrer Policy, Permissions Policy — each graded `missing`/`weak`/`reasonable`/`strong` from its actual value (e.g. a CSP with `unsafe-inline` scores as weak, not as "present = full credit"), not just presence, rolled into the percentage score. `/api/v1/security` additionally returns `security_header_grades` with the per-header breakdown.
🚀 15-Min In-Memory Cache	Cached responses served in < 0.01 ms server-side processing time.
⚡ Multi-Worker + Auto-Reconnect Redis	`uvicorn --workers N` multi-process cluster (set via the `WORKERS` env var; `gunicorn` is a listed dependency for anyone who prefers it as the process manager, but the shipped Dockerfile launches uvicorn directly). Distributed rate limiting via Redis with startup ping validation, automatic reconnect every 30s, and immediate `degraded_fallback` status propagation to `/health/details`.
🔒 Split `/health` + `/health/details`	Minimal public liveness probe (`/health`). Full operational details (Redis mode, status, engine) secured via `HEALTH_DETAILS_SECRET` header on `/health/details`.
🧯 Per-Host Circuit Breaker	Trips after repeated timeouts/connection failures/5xx to one host, fails fast during the cooldown window instead of burning the full connect+read timeout budget on every request, and probes recovery automatically (never trips on ordinary 4xx).
🧩 Request Single-Flight + DNS Coalescing	Concurrent requests for the same URL (or the same hostname's DNS lookup) share one in-flight fetch instead of hammering the origin N times.
🩹 Negative-Result Cache	Short-TTL caching of recent upstream failures (DNS/timeout/5xx) so a broken target fails fast instead of repeating the same slow failure for every request during an outage.
🧱 Adaptive Byte-Limit Hardening	Streaming byte cap is enforced on the decoded chunk, closing a decompression-bomb gap where a small gzip/br payload could otherwise expand to megabytes in a single read. Response headers are also count- and size-bounded.
🏷️ Structured Error Codes	Every error response carries a machine-readable `error.code` / `error.retryable` object (e.g. `SSRF_BLOCKED`, `UPSTREAM_TIMEOUT`, `CIRCUIT_OPEN`) alongside the existing `detail` string — fully additive, v1 contract unchanged.
📈 Prometheus Metrics + Structured JSON Logs	`/metrics` exposes request/cache/SSRF/circuit-breaker/rate-limit counters and latency histograms. Every log line is a JSON object with `request_id` for end-to-end tracing; known-sensitive fields are redacted automatically.
🧠 Confidence-Scored Tech Detection	`/api/v1/tech-stack` now also returns `technology_details`: per-technology confidence score, matched evidence, and category (cms/ecommerce/framework/analytics/payment/hosting/…), alongside the original flat list.
📦 Deeper Product & JSON-LD Parsing	Traverses `@graph` and top-level JSON-LD arrays (not just top-level objects), extracting SKU, MPN, GTIN/ISBN, seller, condition, price range, and images.
🔎 Unicode-Aware SEO & Keywords	Keyword extraction now matches non-ASCII scripts correctly (accented/Cyrillic/etc. content), and the SEO audit adds `lang` attribute, viewport, noindex, multi-H1, Twitter Card, and structured-data checks.

| ⚡ Lazy Extraction Per Endpoint | Specialized endpoints only run the extractors they actually need instead of the full pipeline — `/sec

只显示了开头部分；其余内容请在仓库中阅读