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Deterministic browser automation. Works out of the box with Claude/Codex/OpenCode

474 starsC++

Open-source browser for AI agents (~90% on Mind2Web)

by theredsix·Mar 11, 2026·155 points·55 comments

AI Analysis

●●●BangerWizardryBig BrainZero to One

Forked Chromium to freeze execution state—solves the stale-state problem that breaks most browser agents.

Strengths
  • Freezes JavaScript execution after each action, eliminating race conditions in agent reasoning.
  • Captures structured event summaries alongside screenshots for multimodal agent loops.
  • ~90% on Mind2Web benchmark shows real performance on established evaluation.
Weaknesses
  • Forking Chromium means heavy maintenance burden as upstream evolves.
  • Browser automation for agents is emerging—Browser Use and Playwright compete.
Category
Target Audience

AI agent developers building browser automation

Similar To

Browser Use · Playwright · LangChain Browser Tools

Post Description

Hi HN, I forked chromium and built agent-browser-protocol (ABP) after noticing that most browser-agent failures aren’t really about the model misunderstanding the page. Instead, the problem is that the model is reasoning from a stale state.

ABP is designed to keep the acting agent synchronized with the browser at every step. After each action (click, type, etc), it freezes JavaScript execution and rendering, then captures the resulting state. It also compiles the notable events that occurred during that action loop, such as navigation, file pickers, permission prompts, alerts, and downloads, and sends that along with a screenshot of the frozen page state back to the agent.

The result is that browser interaction starts to feel more like a multimodal chat loop. The agent takes an action, gets back a fresh visual state and a structured summary of what happened, then decides what to do next from there. That fits much better with how LLMs already work.

A few common browser-use failures ABP helps eliminate: * A modal appears after the last Playwright screenshot and blocks the input the agent was about to use * Dynamic filters cause the page to reflow between steps * An autocomplete dropdown opens and covers the element the agent intended to click * alert() / confirm() interrupts the flow * Downloads are triggered, but the agent has no reliable way to know when they’ve completed

As proof, ABP with opus 4.6 as the driver scores 90.5% on the Online Mind2Web benchmark. I think modern LLMs already understand websites, they just need a better tool to interact with them. Happy to answer questions about the architecture, forking chrome or anything else in the comments below.

Try it out: `claude mcp add browser -- npx -y agent-browser-protocol --mcp` (Codex/OpenCode instructions in the docs)

Demo video: https://www.loom.com/share/387f6349196f417d8b4b16a5452c3369

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