A minimalist tool (wexin-read-mcp) enables large language models (LLMs) to read and process content from WeChat official account articles. It overcomes WeChat's anti-scraping measures by simulating a browser environment, offering a solution for LLM-based content analysis and summarization.

How It Works

The project employs Playwright to simulate a complete browser environment, effectively circumventing WeChat's anti-scraping technologies. Subsequently, BeautifulSoup4 parses the HTML to extract crucial article details, including the title, author, publication date, and main body content, which is then relayed to the LLM.

Quick Start & Requirements

• Installation: Execute pip install -r requirements.txt to install Python dependencies.
• Configuration: Modify the provided JSON configuration file to reflect the correct path to the server.py script.
• Prerequisites: Requires Python 3.10+.
• Usage: Integrate with LLMs by invoking the read_weixin_article(url) function.
• Links: No specific documentation or demo links are provided.

Highlighted Details

• Utilizes Playwright for advanced browser simulation to bypass anti-scraping.
• Extracts key article components: title, author, date, and content.
• Prioritizes a concise and minimal code implementation.

Maintenance & Community

The provided README does not include details on maintainers, community channels, sponsorships, or roadmap information.

Licensing & Compatibility

This tool is strictly for personal learning and research and is explicitly prohibited for commercial use. Users must adhere to the WeChat platform's service agreement.

Limitations & Caveats

The tool is restricted to personal learning and research, with commercial use forbidden. Users should maintain a crawl interval exceeding 2 seconds to prevent high-frequency scraping and must comply with WeChat's platform service agreement.