Web Content Extractor (agent Optimized)
@agenson-tools
Web Content Extractor (agent Optimized) について
Agent-optimized MCP server for extracting clean, structured content from web pages
基本情報
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-content-extractor": {
"command": "npx",
"args": [
"@agenson-horrowitz/web-content-extractor-mcp"
]
}
}
}ツール
ツールは検出されませんでした
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 Content Extractor (agent Optimized)?
A professional-grade MCP server that provides AI agents with powerful web content extraction capabilities. It extracts clean, structured, LLM-optimized content from web pages, saving tokens and improving agent accuracy by converting raw HTML into markdown, JSON, or structured data.
How to use Web Content Extractor (agent Optimized)?
Install via npm globally (npm install -g @agenson-horrowitz/web-content-extractor-mcp) or configure it in Claude Desktop or Cline by adding the server to the respective MCP config JSON with command npx and args ["@agenson-horrowitz/web-content-extractor-mcp"]. Once configured, users invoke specific tools such as extract_article, extract_structured_data, extract_links, screenshot_to_markdown, or batch_extract.
Key features of Web Content Extractor (agent Optimized)
- Advanced article extraction with clean markdown and metadata
- Structured data parsing (tables, lists, forms) as JSON
- Intelligent link analysis with categorization and context
- Visual layout analysis via screenshot-to-markdown
- High-performance batch processing with rate limiting
- Sub-2-second response times and token-efficient output
Use cases of Web Content Extractor (agent Optimized)
- AI agent reads and summarizes news articles, blog posts, or research papers
- Extract pricing tables and feature comparisons for competitive analysis
- Perform bulk content audits across multiple competitor websites
- Analyze UI layouts and visual content for design understanding
- Discover and categorize internal/external links for site mapping or SEO
FAQ from Web Content Extractor (agent Optimized)
How does Web Content Extractor (agent Optimized) differ from raw HTML scraping?
It extracts LLM-optimized content with structured metadata, saving tokens and improving accuracy compared to raw HTML. Uses Mozilla Readability, Playwright, and other libraries for clean output.
What are the runtime requirements and dependencies?
Requires Node.js; uses Playwright for browser automation, Mozilla Readability for content extraction, Metascraper for metadata, Turndown for HTML-to-markdown, and JSDOM for DOM manipulation.
Where does the extracted data live?
All data is extracted from provided URLs and returned in the tool response; no persistent storage on the server side is mentioned.
What are the known limits of Web Content Extractor (agent Optimized)?
Average response time < 2 seconds; rate limit of 10 extractions/second (configurable); content limit of 50MB per extraction; free tier allows 500 extractions/month, with higher limits on paid plans.
What transport and authentication options are available?
Uses MCP protocol via stdio transport (default setup via npx). Authentication is not required for local usage; for hosted usage via MCPize or direct API, it supports API keys and crypto micropayments (USDC on Base chain).
「AI とエージェント」の他のコンテンツ
Sequential Thinking Multi-Agent System (MAS)
FradSerAn advanced sequential thinking process using a Multi-Agent System (MAS) built with the Agno framework and served via MCP.
1Panel
1Panel-dev🔥 1Panel is a modern, open-source VPS control panel — and the only one with native AI agent support. Run Ollama models, deploy OpenClaw agents, and manage your entire server stack from one clean web interface.
Gemini MCP Server
aliargunMCP server implementation for Google's Gemini API
🛡️ A.I.G(AI-Infra-Guard)
TencentA full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.
MCP Client for Ollama (ollmcp)
joniglHarness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved pre
コメント