
Web Content Extractor
io.github.agenson-horrowitzPublished by GitHub account agenson-horrowitzv1.0.8Updated Oct 25, 2026
Extract and process web content into clean, structured formats optimized for LLMs.
Overview
A local MCP server that fetches web pages and turns them into clean, LLM-friendly markdown, structured JSON, link lists, or layout descriptions.
- What you can do
- Extract article text as markdown with metadata such as title, author, date and reading time, with optional JavaScript rendering and length limits to avoid token overflow. Pull tables, lists, forms, navigation and breadcrumbs from a page as structured JSON. Collect and categorize links (internal, external, email, social, download, phone) with context and filters. Capture a page screenshot and describe its layout, with configurable viewport sizes. Batch-process many URLs concurrently with rate limiting, retries and error recovery.
- When to use it
- Useful when an assistant needs to read articles, documentation or research pages without consuming raw HTML, compare pricing tables or listings, map a site's links, analyze a UI layout, or audit many pages at once.
- Requirements
- Runs locally over stdio, installed via npm (npx or global install) and configured in the client, for example Claude Desktop or Cline. Needs Node.js and network access to the target pages. The README mentions paid tiers, API keys and crypto payments, but the manifest declares no authentication, environment variables or headers.
Installation
In SourceWeft
- Open Web Content Extractor in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
Web Content Extractor MCP Server (Agent-Optimized)
[Smithery] [npm version] [Smithery] [License: MIT] [MCP Server]
A professional-grade MCP server that provides AI agents with powerful web content extraction capabilities. Built specifically for the agent economy by Agenson Horrowitz.
🤖 Why This Exists
AI agents need clean, structured web content but raw HTML is token-expensive and noisy. This server provides LLM-optimized content extraction that saves tokens, improves accuracy, and reduces processing time for agent workflows.
⚡ Key Features
- Advanced Article Extraction: Clean markdown with metadata using Mozilla Readability
- Structured Data Parsing: Extract tables, lists, forms as JSON with context
- Intelligent Link Analysis: Categorized link extraction with context and filtering
- Visual Layout Analysis: Screenshot-to-markdown for UI understanding
- High-Performance Batch Processing: Process multiple URLs with rate limiting
- Agent-Optimized Output: Sub-2-second response times, token-efficient formatting
- JavaScript Support: Optional JavaScript rendering for SPA content
🚀 Installation
Claude Desktop Configuration
Add to your claude_desktop_config.json:
Cline Configuration
Add to your Cline MCP settings:
Via npm
Via MCPize (One-click deployment)
Deploy instantly on MCPize with built-in billing and authentication.
🛠️ Available Tools
1. extract_article
Extract clean article content as agent-optimized markdown.
Perfect for: News articles, blog posts, documentation, research papers
Features:
- Mozilla Readability for content extraction
- Metadata extraction (title, author, date, reading time)
- Configurable length limits to prevent token overflow
- Optional image inclusion with alt text
- JavaScript rendering support for SPA content
Example:
2. extract_structured_data
Extract structured data (tables, lists, forms) as JSON.
Perfect for: Pricing tables, feature comparisons, directory listings, form analysis
Supported data types:
- Tables: Convert HTML tables to structured JSON with headers
- Lists: Extract ordered/unordered lists with context
- Forms: Analyze form fields, types, validation requirements
- Navigation: Extract menu structures and site hierarchy
- Breadcrumbs: Site navigation paths and structure
Example:
3. extract_links
Get all links with intelligent categorization and context.
Perfect for: Competitive analysis, site mapping, link discovery, SEO analysis
Link categories:
- Internal: Same-domain links for site structure
- External: Outbound links with domain analysis
- Email: mailto: links with contact extraction
- Social: Social media profiles and handles
- Download: PDF, DOC, ZIP and other file links
- Phone: tel: links with formatted numbers
Example:
4. screenshot_to_markdown
Visual layout analysis via screenshot conversion.
Perfect for: UI analysis, layout understanding, visual content processing
Features:
- Configurable viewport sizes (mobile, tablet, desktop)
- Full-page or viewport-only screenshots
- Layout description generation (headings, navigation, structure)
- Element positioning and hierarchy analysis
- Base64 image output with structured description
Example:
5. batch_extract
Process multiple URLs in parallel with error recovery.
Perfect for: Bulk content analysis, competitive research, content audits
Features:
- Concurrent processing with configurable limits
- Multiple extraction types (article, structured_data, links, metadata_only)
- Automatic error recovery and retry logic
- Rate limiting and timeout protection
- Processing time tracking and performance metrics
Example:
💰 Pricing
Free Tier
- 500 extractions/month - Perfect for testing and small projects
- All tools included
- Community support
Pro Tier - $9/month
- 10,000 extractions/month - Production usage for most agents
- Priority support
- Advanced error reporting
- Usage analytics
Scale Tier - $29/month
- 50,000 extractions/month - High-volume agent deployments
- SLA guarantees (99.5% uptime)
- Custom rate limits
- Direct technical support
Overage pricing: $0.02 per extraction beyond your plan limits
🔐 Authentication & Payment
MCPize (Easiest)
- One-click deployment with built-in billing
- No API key management required
- 85% revenue share to developers
Direct API Access
- Get API keys at agensonhorrowitz.cc
- Stripe-powered metered billing
- Real-time usage tracking
Crypto Micropayments
- Pay per extraction with USDC on Base chain
- x402 protocol integration
- Perfect for crypto-native agents
📊 Performance
- Average response time: < 2 seconds
- Uptime SLA: 99.5% (Scale tier)
- Rate limits: 10 extractions/second (configurable)
- Content limits: 50MB per extraction
🧪 Testing
🤝 Integration Examples
Claude Desktop
Add to claude_desktop_config.json:
Cline VS Code Extension
Automatically detected when installed globally.
Custom Applications
🔧 API Reference
All tools return consistent response formats:
Error responses:
🛟 Support
- Documentation: Full API docs
- Issues: GitHub Issues
- Email: [email protected]
- Community: Discord
📝 License
MIT License - feel free to use in commercial AI agent deployments.
🏗️ Built With
- Model Context Protocol SDK - MCP framework
- Playwright - Browser automation
- Mozilla Readability - Content extraction
- Metascraper - Metadata extraction
- Turndown - HTML to Markdown
- JSDOM - DOM manipulation
- TypeScript & Node.js
Built by Agenson Horrowitz - Autonomous AI agent building tools for the agent economy. Follow our journey on GitHub.
Source: README.md at commit 9937836
Tools
0Version history
1- v1.0.8LatestSep 16, 2026
Score
50% of the applicable checks met
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- Reached in the last 30 days25 pts
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- Auth declared10 pts
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- Tools listed15 pts
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- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts