serp.fast

Tabstack

Mozilla's web execution API for AI agents – four endpoints (extract, generate, automate, research) with adaptive routing from raw HTTP fetch to full browser.

Maintained by Nathan Kessler·Updated

Web scraping APIs abstract away the hardest parts of web data collection: JavaScript rendering, anti-bot detection, proxy rotation, and data parsing. Instead of building and maintaining your own scraping infrastructure, you send a URL and receive clean, structured data back. For AI applications, many of these APIs now return LLM-ready markdown or structured JSON.

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Features

JS Rendering
Structured Output
Open Source
Self-Hosted Option
Pricing:FreemiumSee pricing →

Editorial assessment

Built by Mozilla, which is unusual in a category dominated by YC and VC-backed startups. The four-endpoint surface (extract, generate, automate, research) overlaps with Firecrawl, but the technical differentiator is adaptive routing – requests start as raw HTTP fetches and escalate to a full browser only when the page requires JS execution or hydration. Requests identify with a 'Mozilla Tabstack' User-Agent, robots.txt is honored against that agent, and Mozilla commits to no model training on collected content with ephemeral data handling. Currently in public early access. Pricing is competitive at $0.35 per 1k credits pay-as-you-go (10 credits ≈ $0.0035 per markdown extract, 50 credits ≈ $0.0175 per JSON extract, 100 credits per automate action, 250–350 credits per research run), with 10,000 free credits to start and Team ($99/mo, 500K credits) and Pro ($499/mo, 3M credits) tiers above. The product surface is broad for a launch-stage offering – worth evaluating against Firecrawl on actual workloads before committing.

How Tabstack compares

Firecrawl

Firecrawl is the closest analog with a similar multi-endpoint surface (scrape, extract, search, agent) and a much larger track record – 350K+ developers and 48K+ GitHub stars vs. Tabstack's launch-stage adoption.

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