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Crawler For Llm

@KonghaYao

Crawler For Llm について

高等级的免费爬虫MCP, 完全 Markdown 化支持,支持微信公众号等一大批国内网站。A powerful web crawler designed specifically for LLM applications, capable of extracting clean, readable content from various web pages and converting it to Markdown format. This tool is essential for building knowledge bases, training

基本情報

カテゴリ

ブラウザ自動化

トランスポート

stdio

公開者

KonghaYao

投稿者

心屿 江

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": {
    "langgraph-crawler": {
      "command": "npx",
      "args": [
        "-y",
        "@langgraph-js/crawler-mcp@latest"
      ]
    }
  }
}

ツール

2

A powerful web content extraction tool that retrieves and processes raw content from specified URLs, ideal for data collection, content analysis, and research tasks.

A powerful web search tool that provides comprehensive, real-time results using search engine. Returns relevant web content with customizable parameters for result count, content type, and domain filtering. Ideal for gathering current information, news, and detailed web content analysis.

概要

What is Crawler For Llm?

Crawler For Llm is a universal web crawler designed for LLM applications, extracting clean, readable content from web pages and converting it to Markdown. It includes built-in support for the Model Context Protocol (MCP) for enhanced context management, and is intended for building knowledge bases, training data collection, and content aggregation.

How to use Crawler For Llm?

Add the provided MCP server configuration to your project's settings. Use the command npx -y @langgraph-js/crawler-mcp@latest with the server name langgraph-crawler.

Key features of Crawler For Llm

  • Universal web crawler with MCP integration
  • Extracts clean content and converts to Markdown
  • Supports documentation, development, and Chinese platforms
  • Continuously expanding list of supported websites
  • Built for LLM knowledge bases and training data

Use cases of Crawler For Llm

  • Building knowledge bases for LLM applications
  • Collecting training data from diverse web sources
  • Aggregating content from multiple platforms

FAQ from Crawler For Llm

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