psyb0t/docker-stealthy-auto-browse — Stealth browser automation that actually works.

Description and use

Here's a brief summary of the open-source project:

The psyb0t/docker-stealthy-auto-browse project is an open-source, stealthy browser automation tool that allows for remote control and interaction with real tools and data, using a standard protocol. This project enables the connection of AI assistants to real tools and data, facilitating standardized integrations and making it easier to ship Model Context Protocol servers. With its high production readiness, strong adoption, and recent activity, this project is suitable for serious pilots and potential large-scale deployments.

**Value Proposition:**
The psyb0t/docker-stealthy-auto-browse project provides a valuable solution for connecting AI assistants to real tools and data, making it easier to standardize integrations and ship Model Context Protocol servers. This project enables the automation of complex tasks, allowing for more efficient and streamlined workflows.

**Practical Adoption Path:**
To adopt this project, developers can start by evaluating its implementation signals, such as API/SDK/CLI, language metadata, and focused topics. They can also review the project's license, security posture, and active maintainers to ensure it meets their requirements. With its straightforward integration process and recent activity, this project is suitable for serious pilots and potential large-scale deployments.

**Production Readiness:**
The psy

Problem

psyb0t/docker-stealthy-auto-browse helps connect AI assistants to real tools and data through a standard protocol.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Evidence

Stealth browser automation that actually works. Runs Camoufox (custom Firefox) in Docker with zero Chrome DevTools Protocol exposure, real OS-level mouse and keyboard input via PyAutoGUI, and a JSON HTTP API + MCP server to control it all remotely. Watch it live via noVNC.

Source