wechat-article-fetcher

You can automatically rank and save WeChat articles to Obsidian by fetching posts from followed accounts, scoring them against research interests like AI Agent and System Design, and generating a Markdown report with frontmatter appended to your vault.

Yes, you can fetch WeChat articles from specific official accounts or all followed accounts. The tool applies date filtering to retrieve targeted posts and scores them based on keyword tiers matching your research interests.

Keyword scoring for ranking WeChat articles works by evaluating fetched content against predefined tiers of research interests such as AI Agent, System Design, and GitHub Open Source to determine relevance and generate ranked insights.

Yes, retrieving WeChat posts requires MCP integration. The tool implements MCP-based article retrieval to access official account content, apply keyword-based scoring, and output structured Obsidian Markdown reports.

The best way to consolidate WeChat articles based on research interests is using an automated fetcher that scores posts across predefined keyword tiers, ranks them by relevance, and delivers ready-to-use Markdown insights.