No-Code Web Scraping with KnowledgeSDK and n8n (2026)
Build n8n workflows that scrape URLs, search your knowledge base, and send results to Slack — all without writing a backend.
Tutorials, comparisons, and deep-dives on RAG pipelines, LLM data pipelines, and web scraping for production AI systems.
Build n8n workflows that scrape URLs, search your knowledge base, and send results to Slack — all without writing a backend.
Learn to scrape URLs to clean markdown, build a semantic search index, and subscribe to webhooks using the KnowledgeSDK Python SDK with async support.
Build a Next.js chat app that scrapes URLs and searches knowledge using Vercel AI SDK tool calling and KnowledgeSDK, with full streaming support.
Build a LangChain agent with live web access using knowledgeSDK. Two approaches: knowledgeSDK as a LangChain tool, and adding semantic search for querying scraped content.
Build a lead enrichment pipeline that scrapes company websites, extracts structured data—description, pricing, tech stack—and feeds it directly into your CRM.
Bad markdown ruins RAG quality. Learn how to identify common extraction failures, measure markdown quality, and ensure clean output for LLMs.
Build an AI news aggregator that scrapes any tech site, categorizes articles semantically, deduplicates stories, and delivers a daily brief—no RSS required.
RAG or fine-tuning? A practical decision guide covering costs, update frequency, and when web scraping feeds your LLM better than baked-in training.
Most RAG systems are frozen at ingestion time. Learn how to add a live web layer to your pipeline for hybrid retrieval that combines long-term memory with real-time data.
Build a multi-step research agent using LangChain and KnowledgeSDK that takes a question, scrapes sources, searches semantically, and synthesizes answers with citations.
A complete guide to scraping any website to clean markdown in 2026. Covers static pages, React SPAs, paginated content, and Cloudflare-protected sites with code examples.
BM25 vs embeddings for RAG: when semantic search wins, when keyword search wins, and why hybrid search is almost always the right answer.