Blog
Tutorials, comparisons, and insights for AI teams.
How to Track an Online Store's Prices on a Daily Schedule
Target a store's product grid with a CSS selector, schedule a daily crawl, and build your own price-history tracker by diffing each day's export. A practical, honest walkthrough of what FireScraper does — and what your code does.
How to Automate Your Pipeline with the Completion Webhook
Get a signed POST the moment a crawl's exports are ready, so your own code can run automatically — embed the data, diff prices, or load a database. The event-driven glue for building a real scraping pipeline.
How to Scrape a Specific List of URLs (Not a Whole Site)
Have a hand-picked set of pages — product URLs, competitor pages, specific articles? Paste them all in and FireScraper scrapes exactly those, no crawling. One clean record per URL.
How to Monitor a Competitor's Pricing or Changelog on a Schedule
Turn any crawl into a recurring job that runs daily, weekly, or monthly — so you always have a fresh snapshot of a competitor's pricing page, a changelog, or any site you need to keep an eye on.
How to Build a Content Index of an Entire Website as JSON
Use structured extraction to pull every page's title, description, language, and word count into one clean JSON index — ideal for content audits, search indexes, and site inventories.
How to Extract Product & Listing Details into Structured JSON
Define a simple JSON schema and FireScraper pulls labeled fields — price, availability, SKU, and more — out of every page into clean, typed records. Perfect for product pages, listings, and spec sheets.
How to Extract Just the Content You Want with CSS Selectors
Use a content CSS selector to tell FireScraper exactly which part of each page to keep — the article body, a product description, or a specific component — and drop the rest of the page entirely.
How to Build a Training Corpus from a Website (Documents JSONL)
Crawl a website and export one clean JSON record per page — full text plus rich metadata — as JSONL. The ideal starting point for a fine-tuning corpus, a document store, or your own chunking pipeline.
How to Build a RAG-Ready Dataset from Any Website (Chunks JSONL)
Crawl a docs site, blog, or knowledge base and export it as pre-chunked JSONL — clean, embedding-sized passages with stable IDs and metadata, ready to drop straight into a vector database. No splitting code required.
How to Scrape a Website into a CSV Spreadsheet
Crawl an entire website and export every page as a CSV you can open in Excel, Google Sheets, or pandas — one row per page, with titles, word counts, links, and full text. No code required.
How to Save an Entire Website as Clean Markdown
Crawl any website and export every page as clean, readable Markdown — perfect for offline reading, note-taking apps like Obsidian and Notion, or feeding into an LLM.
FireScraper Python SDK: Sync, Async, and LangChain Integration
The FireScraper Python SDK is now on PyPI. Use it to scrape websites from Python scripts, async pipelines, and LangChain RAG workflows with a single pip install.
Web Scraping for AI Agents: Feeding Data to Autonomous Workflows
How AI agents can use FireScraper's API, webhooks, and scheduled crawls to autonomously gather and refresh web data for their workflows.
How to Use Structured Extraction to Build a Knowledge Base
Define a JSON schema, point FireScraper at a website, and get typed, consistent data from every page — no post-processing required.
FireScraper vs Crawl4AI: Managed API vs Open Source
Comparing FireScraper's managed scraping platform with Crawl4AI's open-source framework — when to choose each for your AI data pipeline.
FireScraper vs Apify: Which Scraping API for AI Teams?
Comparing FireScraper and Apify — pricing, complexity, and which is the better fit for AI teams who need clean text for RAG pipelines.
FireScraper vs Firecrawl: Which Web Scraping API for Your RAG Pipeline?
An honest comparison of FireScraper and Firecrawl — pricing, features, and which is the better fit for AI teams building RAG pipelines.
Markdown vs JSONL vs CSV: Choosing the Right Export Format for Your LLM Pipeline
Each export format serves a different purpose in AI workflows. Here is when to use Markdown, JSONL, CSV, JSON, and ZIP exports from your web scraping pipeline.
How to Build a RAG Pipeline with FireScraper
Step-by-step guide to crawling websites, exporting clean text, and loading it into a vector database for retrieval-augmented generation.
Best Web Scraping APIs for AI in 2026
A developer's guide to the top web scraping APIs built for AI teams — comparing pricing, features, and output formats for RAG pipelines and LLM training.
Introducing FireScraper: Web Scraping Built for AI Teams
FireScraper turns any website into clean, structured text for RAG pipelines, fine-tuning datasets, and AI agent workflows. Here is what makes it different.