The legacy LinkedIn scraping tool. For Yalc workflows, Unipile costs less and ships better data because it uses the LinkedIn API rather than browser automation. Use PhantomBuster only if you need a specific phantom Unipile doesn't cover.
PhantomBuster is a marketplace of pre built browser automations called Phantoms. Each Phantom does one job: scrape LinkedIn search results, pull profile visitors, send connection requests, scrape Twitter, search Google Maps, and so on. 100+ Phantoms cover most repetitive web tasks GTM teams need.
For Yalc workflows, PhantomBuster's value has eroded. Most of the LinkedIn use cases (profile scraping, post engagement, connection requests, messaging) are now better served by the Unipile API which is faster, cheaper, and uses LinkedIn's actual API rather than browser automation. PhantomBuster remains useful for non LinkedIn web automation (Google Maps, Twitter, etc.) where Unipile doesn't compete.
PhantomBuster sits at the **intake** node for the niche of web automation tasks Unipile doesn't cover. Most Yalc operators end up using PhantomBuster sparingly, only for one off scrapes outside the LinkedIn surface.
The framing is: if Unipile can do it, use Unipile. If only PhantomBuster has the Phantom you need, use PhantomBuster but cap the budget tightly because execution hours run out fast.
The fallback automation layer for non LinkedIn surfaces. Yalc operators install PhantomBuster only when a specific Phantom is needed and the cost makes sense.
Copy paste prompts for Claude Code that invoke PhantomBuster.
No first party Yalc skill ships for PhantomBuster. Yalc's LinkedIn coverage is via Unipile (faster, cheaper, more stable). The few Yalc workflows that touch PhantomBuster do so via Claude's HTTP tool calling the PhantomBuster REST API directly.
→ Request a Yalc skill for this toolPhantomBuster bills monthly across three tiers. The Starter at $69 a month gives you 20 execution hours, 5 phantom slots, and 500 email credits. Pro at $159 a month bumps to 80 hours and 15 slots. Team at $439 a month covers 300 hours and 50 slots. Annual billing reduces these by roughly 20 percent.
The cost reality: execution time is the limiter. A LinkedIn profile scrape consumes 0.8 to 1 minute per profile. 1000 profiles is roughly 13 to 17 minutes. Real world consumption runs 30 to 50 percent higher because of rate limits and retries. Budget assumes you'll consume more than the math suggests.
20 exec hours, 5 phantom slots, 500 email credits. Right for solo operators piloting.
80 exec hours, 15 phantom slots. Right for active outbound teams.
300 exec hours, 50 phantom slots. Right for agencies running parallel workflows.
Starter $69/mo for 20 execution hours, Pro $159/mo for 80 hours, Team $439/mo for 300 hours. Annual billing knocks roughly 20 percent off. Email credits are bundled separately on each plan.
Unipile uses LinkedIn's actual API; PhantomBuster automates a browser. Unipile is faster, cheaper per action, more stable. PhantomBuster remains useful only for niche use cases Unipile doesn't cover or for non LinkedIn surfaces.
0.8 to 1 minute per profile in PhantomBuster. 1000 profiles is roughly 13 to 17 minutes of execution time. Real world overhead from rate limits and retries pushes that to 20 to 25 minutes typically.
Yes via specific Phantoms. Unipile does this faster and cleaner via the API. For Yalc workflows, the linkedin-scraping skill (Unipile based) replaces the PhantomBuster Phantom equivalents.
Account risk on LinkedIn comes from behavioral patterns. PhantomBuster's browser automation is more detectable than Unipile's API approach. Stay below LinkedIn's per day limits (20 to 40 invites, 100 messages) regardless of tool.
Enough for one or two small scrapes and a connection request test. Not enough to see the long tail of issues (LinkedIn UI changes breaking Phantoms, execution time overhead at scale). Validate carefully before annual billing.
Or fork the repo and contribute one.