Compare/Extractor vs Kampala

AI tool comparison

Extractor vs Kampala

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

E

Developer Tools

Extractor

Robust LLM-powered web content extraction

Ship

100%

Panel ship

Community

Free

Entry

Extractor uses LLMs to reliably extract structured data from any webpage. Unlike traditional scrapers that break when HTML changes, Extractor understands the content semantically.

K

Developer Tools

Kampala

MITM proxy that reverse-engineers any app into a stable, callable API

Ship

75%

Panel ship

Community

Free

Entry

Kampala, built by Zatanna AI (YC W26), is a macOS proxy tool that sits between your applications and the internet, intercepts every HTTP/HTTPS request, and automatically reverse-engineers the underlying API. It traces authentication chains — tracking tokens, cookies, and session state — and replays flows on demand, preserving original TLS fingerprints so services can't distinguish API calls from the real app. The key insight is that almost every app that lacks a public API still has a private one — and it's usually more stable than the UI. Kampala targets automation engineers, QA teams, and AI agent builders who need reliable machine-readable access to apps that haven't opened their APIs. Setup is a local MITM cert install; no cloud proxy involved. Currently macOS-only with a Windows waitlist. The team emerged from YC's Winter 2026 batch with backing from Y Combinator. Pricing is in early access, with a free tier planned for solo developers and paid plans for teams building production automations.

Decision
Extractor
Kampala
Panel verdict
Ship · 3 ship / 0 skip
Ship · 3 ship / 1 skip
Community
No community votes yet
No community votes yet
Pricing
Free (open source)
Free (early access)
Best for
Robust LLM-powered web content extraction
MITM proxy that reverse-engineers any app into a stable, callable API
Category
Developer Tools
Developer Tools

Reviewer scorecard

Builder
80/100 · ship

Traditional web scraping is brittle. LLM-powered extraction that understands content structure is the right approach. Works on messy pages where CSS selectors fail.

80/100 · ship

This is the tool I've been building in-house at three different companies and never had time to productize properly. The auth chain tracing alone — tracking token refresh flows and session state automatically — would have saved me hundreds of hours. If it works as advertised, it's an instant ship for anyone doing integration work.

Skeptic
80/100 · ship

The LLM cost per extraction makes it expensive at scale. But for high-value data extraction where accuracy matters more than cost, it is worth it.

45/100 · skip

Terms of service violations are a real concern here. Most apps explicitly prohibit automated access through their private APIs, and companies like LinkedIn and Instagram have sued over exactly this pattern. The MITM cert requirement also opens a broad attack surface. Wait for a clearer legal stance before building production systems on this.

Futurist
80/100 · ship

Web scraping becomes web understanding. As more AI agents need to read the web, tools like Extractor become essential infrastructure.

80/100 · ship

The long-term story here is about AI agents needing reliable access to every app humans use. We can't wait for every SaaS to ship an official API. Tools like Kampala are how AI agents will integrate with the existing software ecosystem for the next five years, until MCP-style universal interfaces catch up.

Creator
No panel take
80/100 · ship

For social media automation and cross-platform content workflows this is a game-changer. Building automations for platforms with limited or expensive APIs has always required fragile browser scraping — having a stable API layer extracted from the real app traffic is a much better foundation.

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