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Web Scraping with Anthropic’s MCP Server

@luminati-io

基本情報

カテゴリ

ブラウザ自動化

トランスポート

stdio

作者

luminati-io

Web Scraping with Anthropic’s MCP Server について

Example MCP server and instructions for connecting Anthropic LLMs to external web scraping tools, with real-world examples and Bright Data integration.

Web Scraping with Anthropic’s MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "web-scraping-mcp": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "mcp-amazon-scraper"
      ]
    }
  }
}

Web Scraping with Anthropic’s MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Web Scraping with Anthropic’s MCP?

This guide explains how to build and run an MCP (Model Context Protocol) server for on-demand web data extraction, enabling LLMs like Claude to retrieve live information from websites. It uses Python, Playwright, and lxml to create a server that scrapes Amazon product pages, and it covers connecting the server to development tools like Cursor or Claude Desktop. It also introduces Bright Data’s MCP for professional-grade extraction.

How to use Web Scraping with Anthropic’s MCP?

Set up a Python 3 virtual environment, install dependencies (pip install mcp playwright lxml, then python -m playwright install), and create a file amazon_scraper_mcp.py using the provided code. Run the server, then connect it via an MCP client in Cursor or Claude Desktop. The server exposes two tools: fetch_page (downloads HTML) and extract_info (parses structured data from saved HTML).

Key features of Web Scraping with Anthropic’s MCP

  • fetch_page tool downloads HTML via Playwright headless browser.
  • extract_info tool parses product data using lxml XPath selectors.
  • Handles JavaScript-heavy pages with configurable delays.
  • Saves HTML to a temporary file for structured extraction.
  • Designed for Amazon product pages but adaptable to any URL.

Use cases of Web Scraping with Anthropic’s MCP

  • Extract real-time product details (price, title, description) from Amazon.
  • Enable LLMs to answer questions based on current web data.
  • Automate data collection for price monitoring or comparison sites.
  • Integrate live web scraping into AI assistants and IDEs.

よくある質問

1

What is MCP?

Model Context Protocol (MCP) is an open standard by Anthropic that allows LLMs to interact with external tools, APIs, and data sources in a consistent, secure way. It uses a JSON-RPC interface over transports like `stdio`.

2

Why does an LLM need an MCP server for web scraping?

LLMs cannot naturally browse the internet or fetch live data. MCP provides a standardized bridge that lets them call tools to download and extract information from websites on demand.

3

What dependencies are required?

Python 3, the MCP Python SDK (`mcp`), Playwright for browser automation, and lxml for HTML parsing. Playwright browser binaries must be installed separately.

4

What tools does this server expose?

It

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