Provides personalized CSS learning updates by tracking known concepts in memory, fetching latest CSS news via Perplexity, and guiding users through new CSS features they haven't learned yet.
Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.
Tracks learning progress and generates personalized daily learning insights using RAG to fetch relevant content from blogs, RSS feeds, and Reddit based on your current topics and learning goals.
A companion MCP server that makes CSS legible to AI agents by resolving cascade, tracing properties, and explaining what applies and why before an agent modifies styles.
Provides up-to-date CSS documentation and browser compatibility data from MDN through natural language queries. Features intelligent caching and supports all CSS properties, selectors, functions, and concepts with automatic normalization.
Provides access to curated AI news feeds and the ability to fetch and normalize any RSS/Atom/RDF feed, enabling AI agents to consume up-to-date content.