Fetch a web page, and use a local Qwen model to extract/answer question about its full content. Long pages are automatically split into chunks and analyzed piece by piece (map-reduce), so no content is skipped.

Reports progress while working (page fetch retries, per-chunk analysis), so a client that respects MCP progress notifications won't time out waiting on a long page -- this can take 30s-3min or more.

Args: url: The page to fetch and analyze. question: What to extract or answer about the page's content.

Search a specific site for pages/listings containing phrase, then run analyze_page-style extraction on each match to answer question.

Works on any site without site-specific scraping code: it uses DuckDuckGo's site: search to find matches, then trafilatura + Qwen to read and filter each page's content, so it keeps working even if the site's layout changes.

Each match takes roughly 30s-3min to fetch and analyze (more for long pages), so a large max_results will take proportionally long to return. Progress is reported per match and per chunk, for MCP clients that respect it.

Args: site: Domain to search within, e.g. "example.com". phrase: Exact phrase the publication/listing must contain. question: What information to extract from each matching page. max_results: Max number of matching pages to analyze (default 5).

List the Qwen/Ollama models currently available on the local Ollama server.