Site Reader

Site Reader is a web data contextualization service for LLMs that turns any website into structured, semantically cleaned Markdown context ready for vector indexing or direct use in a language model.

Instead of manual parsing and preprocessing, it runs a pipeline of specialized agents:

• fetch_url — collect site data
• clean_html — remove navigation, ads, scripts, and visual noise
• extract_semantics — extract headings, metadata, content hierarchy, and semantic blocks
• chunk_md — semantic chunking into logical segments while preserving cross-links
• enrich_metadata — add URL, update date, category, and tags for precise search
• validate_output — check integrity, readability, and Markdown standards compliance

The service helps AI agents, chatbots, and RAG systems work with up-to-date site information without hallucinations or stale data, and addresses key web-content integration pain points: lost structure during parsing, noise in raw HTML, difficulty keeping content fresh after site updates, lack of a unified format for pipelines, and manual work preparing data for LLMs.