Based on a tutorial by Tuyến AI Pro
Are you tired of manually copying and pasting content from websites just to summarize or rewrite articles using AI? If you’ve been doing this repetitive task by hand, you’re probably wondering if there’s a better way to automate the entire process.
I’ve been there too, and that’s exactly why I’m breaking down this excellent tutorial from Tuyến AI Pro. This comprehensive guide shows you how to completely automate web content extraction and AI-powered summarization using N8N workflows – no more manual copy-pasting required!
Quick Navigation
- The Problem with Manual Content Extraction (00:00-02:30)
- Two Automation Methods Compared (02:31-04:15)
- Method 1: HTML CSS Selector Approach (04:16-08:45)
- Method 2: MCP Server with Firecrawl (08:46-12:30)
- Setup Requirements & Prerequisites (12:31-15:20)
- N8N Installation & Update Guide (15:21-18:45)
- Workflow Configuration & API Setup (18:46-25:30)
- Testing Both Methods Live (25:31-32:15)
- Customization & Advanced Tips (32:16-35:00)
The Problem with Manual Content Extraction
Most people are stuck in an inefficient workflow when it comes to content summarization. The typical process involves manually copying content from websites like VNExpress, pasting it into ChatGPT, Grok, or Gemini, and then asking the AI to rewrite or summarize the content.
Key Problems with Manual Approach:
- Time-consuming copy-paste operations
- No automation possibilities
- Repetitive manual work for each article
- Inconsistent formatting and results
My Take:
This manual approach becomes especially painful when you’re processing multiple articles daily for social media or blog content. The automation methods shown in this tutorial can save hours of work weekly.
Two Automation Methods Compared
Tuyến AI Pro demonstrates two distinct approaches to automating content extraction, each with its own advantages and limitations.
Method 1: HTML CSS Selector Extraction
- Directly extracts content using specific HTML selectors
- Requires manual configuration for each website structure
- Need to identify exact CSS classes and HTML tags
- Less flexible when switching between different news sources
Method 2: MCP Server with Firecrawl
- Uses AI-powered content extraction
- Works across different website structures automatically
- More flexible and adaptable to various sources
- Requires MCP server setup and Firecrawl API
Method 1: HTML CSS Selector Approach
The first method demonstrates direct HTML parsing using CSS selectors to extract specific content elements from web pages.
Step-by-Step Process:
- Input the target URL (e.g., VNExpress article)
- Extract HTML content from the webpage
- Use CSS selectors to identify title and content elements
- Process through OpenAI GPT-4o to clean HTML and convert to Markdown
- Generate final summarized content
My Take:
While this method works well for consistent sources, you’ll need to inspect HTML and modify selectors for each different website structure. For example, VNExpress uses “h1.title_detail” while Dân Trí might use completely different classes.
Method 2: MCP Server with Firecrawl
The second approach uses MCP (Model Context Protocol) server with Firecrawl API to intelligently extract content without manual HTML configuration.
Advantages of This Method:
- Automatically adapts to different website structures
- Extracts additional metadata like descriptions
- No need to configure CSS selectors manually
- Works consistently across various news sources
The demonstration shows how this method successfully extracts content from both VNExpress and Dân Trí without any configuration changes, including metadata that the first method missed.
Setup Requirements & Prerequisites
Before implementing either workflow, you’ll need several components properly configured on your system.
Essential Requirements:
- N8N version 1.88 or higher (for MCP server support)
- OpenAI API account with minimum $5 credit
- Firecrawl account (500 free credits for new users)
- Domain setup for cloud deployment (recommended ~$2 cost)
My Take:
The cost barrier is quite low here – under $10 total to get started with a powerful automation system. The Firecrawl free credits alone provide plenty of testing opportunities.
N8N Installation & Update Guide
For users with existing N8N installations, specific update commands are provided to ensure compatibility with MCP server functionality.
# For CPU-based installations
docker-compose down
docker-compose pull
docker-compose up
# For GPU-based installations
docker-compose --profile gpu down
docker-compose --profile gpu pull
docker-compose --profile gpu up
Verification Steps:
- Check N8N version in About section (should be 1.88+)
- Install community node: @n8n/n8n-nodes-firecrawl
- Accept installation risks for community nodes
- Verify successful installation with checkmark indicator
Workflow Configuration & API Setup
The tutorial provides detailed steps for configuring both API connections and workflow settings.
Firecrawl API Configuration:
- Copy API key from Firecrawl dashboard
- Configure MCP server with proper headers
- Set up cURL authentication in playground
- Activate the MCP server in production mode
OpenAI API Setup:
- Create API key in OpenAI platform
- Configure credentials in N8N
- Set up project association and secret key
- Verify connection with green status indicator
My Take:
The configuration process is straightforward once you understand the flow. The most crucial part is ensuring your MCP server URL is correctly configured for your specific N8N installation.
Testing Both Methods Live
The tutorial includes live testing of both workflows using different Vietnamese news sources to demonstrate their effectiveness and limitations.
Test Results Comparison:
- Method 1 successfully extracts from VNExpress but fails on Dân Trí without selector modifications
- Method 2 works seamlessly across both sources without configuration changes
- Content quality and completeness varies between methods
- Processing speed and reliability differences observed
The live demonstration clearly shows why the MCP server approach is more versatile for multi-source content extraction, while the CSS selector method offers more control for specific, consistent sources.
Customization & Advanced Tips
The final section covers how to customize the workflows for different use cases and output requirements.
Customization Options:
- Modify instruction prompts for different summarization styles
- Adjust output length (10, 20, or 30 lines)
- Switch between English and Vietnamese instructions
- Configure different extraction targets (products, specific content types)
Integration Possibilities:
- Connect to social media posting workflows
- Integrate with WordPress for automatic blog publishing
- Set up scheduled content processing
- Chain multiple AI processing steps
My Take:
The real power of this system emerges when you chain it with other automation workflows. Imagine automatically extracting trending articles, summarizing them, and posting to multiple social platforms – all without manual intervention.
