Olostep

Olostep is a pragmatic, no-frills web data API that understands its audience: developers building AI agents that need reliable, clean web data without the operational headache of managing proxies and headless browsers. The product covers the core capabilities you'd expect — scrape, crawl, map, search, answer, and monitor — all behind a single, object-oriented API with native Python and Node.js SDKs, a CLI, an MCP server, and drop-in skills for coding agents like Claude Code, Cursor, and Windsurf. That breadth is a real strength: you don't need to stitch together multiple vendors to search, extract, and monitor. What stands out is the pricing. The free trial gives you 500 requests (all JS-rendered with residential IPs), which is enough to validate the core use case without a credit card. Paid plans start at $9/month for 5,000 requests — that's remarkably cheap compared to competitors like Firecrawl, which typically start at $19/month for the same volume. Per-request costs drop as you scale: Standard (200K requests) works out to $0.399 per 1K, and Scale (1M requests) at $0.399 per 1K as well. The credit packs (10K for $20, 250K for $200, 2M for $1000) are a nice touch for spiky usage, though they're not as cost-efficient as the subscription at high volume. The June 2026 storage parameter is a meaningful differentiator. Most web data APIs treat results as ephemeral — you get your response and the data disappears within hours. Olostep now lets you persist extraction results for 10 days to indefinite, with a default ~7-day retention when you don't specify it. That's a genuine asset for teams building time-series datasets, compliance archiving, or reproducible AI/ML pipelines. The roadmap shows cold storage (AWS Glacier) and a SQL-like query interface coming next, which would turn stored extractions into a queryable database. Where Olostep falls short is on the enterprise front. There's no SOC2 compliance mentioned anywhere, and the docs don't indicate on-prem deployment options. That will rule out banks, healthcare, and other regulated industries that demand those certifications. Also, the free tier is tiny (500 requests) — if you're just poking around, you'll hit the limit quickly. And the per-request cost, while low, climbs if you use credit packs for large one-off jobs (2M credits at $1000 is $0.50/1K vs. $0.40/1K on subscriptions). For AI coding agents, the MCP server and skills are a strong value-add. You can give Claude Code or Cursor native web access without writing any glue code — just `olostep add skills` and your agent knows how to search, scrape, and answer. That's a smooth onboarding experience for the primary audience. Compared to alternatives: Firecrawl is the most direct competitor, with similar capabilities and a more established brand, but at a higher price and with a per-request cost that doesn't drop as dramatically. Apify is broader (more actors, more integrations) but can get expensive as you scale, and its learning curve