CloakHQ/CloakBrowser
CloakBrowser
Stealth Chromium that passes every bot detection test. Drop-in Playwright replacement with source-level fingerprint patches. 30/30 tests passed.
Usage guide
CloakBrowser is an open-source project around ai-agents, anti-detect, antidetect-browser with 26,305 GitHub stars. This guide focuses on when to use it, how to install it, how to run the first example, and what to verify before adopting it.
Key features
- Implemented mainly in Python, useful for judging integration effort in a similar stack.
- GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
- The project has a homepage, so cross-check docs, examples, and release information beyond GitHub.
Best for
- Evaluating CloakBrowser for Python AI workflows.
- Comparing a GitHub project with 26,305 stars and current repository activity.
Pros
- CloakBrowser has visible GitHub traction with 26,305 stars. Topics: ai-agents, anti-detect, antidetect-browser.
- The project provides an external homepage for deeper evaluation.
Cons
- Production fit still depends on documentation depth, issue activity, and release cadence.
- License review should confirm the MIT terms fit your use case.
Production readiness
CloakBrowser should be validated with its README, release history, open issues, and integration requirements before production use.
License risk
MIT is reported by GitHub; review the repository license before redistribution or commercial use.
CloakBrowser architecture preview
CloakBrowser's main path starts at the entry surface, runs through Agent orchestration runtime, combines LLM / model client, Runtime context, Browser automation, and returns User-facing result.
Entry
Web / product entry
Users start from a web UI, hosted product surface, or browser-based workflow.
https://cloakbrowser.dev/
Runtime
Agent orchestration runtime
The orchestration layer plans tasks, calls tools, manages context, and decides the next action.
agent workflow
Model
LLM / model client
The project connects its core runtime to local models or hosted AI APIs when model inference is required.
model signal
Context
Runtime context
Runtime state, user input, repository files, or configuration provide context for each task.
context signal
Tools
Browser automation
Tool adapters let the runtime act outside the model through Browser automation.
Browser automation
Output
User-facing result
The final output is returned to the user, workflow, API caller, or downstream system.
output
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Install tutorial
Before you install
- Python runtime and an isolated virtual environment
- Node.js and the package manager used by the project
- Docker Engine with enough disk space for images and volumes
- A clean working directory for the first test run
Check the runtime environment
CloakBrowser has Docker in the setup path. Confirm Docker Engine works and reserve enough disk space for images and volumes.
Get the project files
Start from the official repository or package so the first run matches the documented behavior.
$ git clone https://github.com/CloakHQ/CloakBrowser.gitInstall or build dependencies
Run the next setup command detected from the project documentation.
$ pip install cloakbrowserAdoption guidance and sources
Practical use cases
Agent workflow prototype
Use it to validate task decomposition, tool calling, memory, tool permissions, and result review loops.
Stealth Chromium that passes every bot detection test. Drop-in Playwri
This is one of the documented reasons to evaluate CloakBrowser before choosing a stack.
Focus area: ai-agents
This is one of the documented reasons to evaluate CloakBrowser before choosing a stack.
AI Agents project comparison
Compare CloakBrowser with similar projects before committing to a stack.
Before adopting
- Complete one clean-environment verification using the official CloakBrowser setup path.
- Review repository license, model weights, external services, and dependency terms for your use case.
- Check recent commits, release cadence, issue response, and documentation depth.
- Evaluate output quality, latency, resource usage, and recovery behavior with a small dataset.
Configuration notes
- Check exposed ports, mounted volumes, and environment variables before running the container in a shared environment.
Sources checked
These links are used to verify repository, documentation, or tutorial details. Review the source pages before adopting the project.
Troubleshooting
- If installation fails, first confirm the command is being run from the README-specified directory.
- If dependencies conflict, retry in a fresh virtual environment, container, or working directory.
- If output looks wrong, return to the smallest documented CloakBrowser example before adding complex data.
- For keys, model files, or external services, verify environment variables, local paths, and permissions one by one.
- Before production use, review recent updates, open issues, license terms, and safety boundaries.
What is CloakBrowser?
CloakBrowser is an open-source ai agents project. Stealth Chromium that passes every bot detection test. Drop-in Playwright replacement with source-level fingerprint patches. 30/30 tests passed.
How do I install CloakBrowser?
Start with the official README. The first detected setup step is: git clone https://github.com/CloakHQ/CloakBrowser.git.
Is CloakBrowser beginner-friendly?
If you already know the Python ecosystem, start with the smallest example. Otherwise test it in an isolated environment first.
Can CloakBrowser be used commercially?
GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
Does CloakBrowser need a GPU?
GPU requirements depend on the workload, model, and dataset size. Start with the smallest README example before scaling up.
How should I decide whether to adopt CloakBrowser?
Evaluate setup cost, maintenance activity, issue health, license terms, and fit with your real workflow.