ai huntt

FetchFox

Freemium

Scrape websites with natural language prompts, get structured JSON back through an API, SDK, or workflow integration, with browser rendering and proxy handling built in.

infoAbout FetchFox

FetchFox is an AI web scraping platform that extracts structured data from websites using natural language prompts, designed for developers and data teams. Users submit a URL pattern and a field description, and the service returns clean JSON rather than raw HTML, handling both static pages and JavaScript-rendered content through browser-based visits. The platform offers multiple interfaces: a JavaScript SDK for Node and TypeScript, direct HTTP API calls, Python support for notebooks and backend scripts, and integrations with workflow tools including n8n, Zapier, and Make. It also provides an MCP server that exposes FetchFox as callable tools for AI agents, and OpenClaw-style agent workflow connections. Output formats include HTML, text, Markdown, links, images, and extracted fields. Specialized APIs provide normalized data from specific sources including Walmart, Amazon, ChatGPT, Home Depot, YouTube, and Google Search. Use cases span e-commerce assortment and pricing monitoring, AI agent context gathering, market intelligence, fintech research, go-to-market account research, and cybersecurity investigations. The vendor reports the product suits teams that want to avoid maintaining custom parser infrastructure. Pricing starts with a pay-as-you-go tier at $0/month with usage at standard rates, or a $10/month subscription with 50% lower per-request costs. Custom enterprise plans are available. The service scales concurrency based on plan level, with no long-term contract required for self-serve users.

checkPay as you go: Buy credits only when you need them
checkUsage runs at 2x current prices
checkVisit calls: $2 per 1k
checkExtract calls: $4 per 1k

thumb_upPros10

  • Multi-level scraping with automatic URL following
  • Natural language extraction instead of manual selectors
  • Multiple AI provider support (OpenAI, Google, OpenRouter)
  • Simple environment variable or in-code API key setup
  • Handles non-uniform pages that break traditional scrapers
  • Can extract subjective data like tone/summaries, not just structured fields
  • Flexible speed controls for different site protections
  • Free with own API key, open source
  • Two-step LLM approach for link discovery then content extraction
  • Chrome Extension integration keeps workflow friction low

thumb_downCons10

  • No discussion of error handling or failure modes
  • No mention of rate limiting or anti-bot protections
  • Unclear what happens when AI extraction hallucinates
  • Documentation is minimal beyond basic usage
  • Benchmark claims are self-reported without independent verification shown
  • Backend-hosted version will likely become paid
  • LLM-based approach means per-page costs and latency vs traditional scrapers
  • Creator admits some sites like LinkedIn still require slow, careful scraping
  • No compliance/security posture disclosed in source
  • Deployment model unspecified—cloud vs self-hosted unknown