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Dev tools · May 9, 2026

Mochi.js: bun-native high-fidelity browser automation library

Hi HN, I’m sharing mochi.js (https://github.com/0xchasercat/mochi), a Bun-native, raw-CDP browser automation framework. It's designed to make programmatic browser use more effective by focusing on consistency and measured parity with regular traffic, purely from the JS layer, against stock Chromium. The most common forms of browser automation focus heavily on client-side line by line probes, which are mostly cosmetic. This makes people feel better but it doesn't have much relevance to actual WAF or anti-automation defences. Mochi.js focuses on what actually matters,…

Mochi.js: bun-native high-fidelity browser automation library launched on May 9, 2026 with 47 votes, #777 of 20,538 launches that month and more than 95% of that year's launches.

Visit mochijs.com ↗Alternativestop 4% of May 2026

In plain words

Mochi.js is a Bun-native browser automation library built on raw Chrome DevTools Protocol that focuses on mimicking legitimate browser traffic to evade detection systems. Designed for developers who need to automate browser interactions, it prioritizes consistency and parity with regular user behavior rather than cosmetic anti-detection measures. The framework targets web application firewalls and anti-automation defenses by analyzing actual detection mechanisms and operating directly from the JavaScript layer against standard Chromium.

written from the facts on this page · September 2026

From the sources

Bun-native, raw-CDP browser automation. Relational fingerprint locking, JIT-installed spoofing, Chromium-native fetch. Leaves no crumbs.

mochi.js is a Bun-native, raw-CDP browser automation framework. Pass a seed and a profile; get a relationally-coherent fingerprint that survives a getParameter(0x9245) probe. JIT-friendly inject payload, Chromium-native fetch (real Chrome JA4 by definition), behavioral synth on top of Bezier+Fitts. Leaves no crumbs. Where Playwright and Puppeteer leave fingerprints, mochi.js leaves nothing measurable. Each pillar covers one class of detection. Every fingerprint surface — canvas, WebGL, audio, fonts, MediaDevices, WebGPU — derives from a single (profile, seed) pair through a 48-rule DAG. No Frankenstein fingerprints; a Mac UA never lands next to Linux WebGL. session.fetch() routes through…from mochijs.com

In the maker’s words, at launch

Hi HN, I’m sharing mochi.js (https://github.com/0xchasercat/mochi), a Bun-native, raw-CDP browser automation framework. It's designed to make programmatic browser use more effective by focusing on consistency and measured parity with regular traffic, purely from the JS layer, against stock…

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