vessel-browser
Enables AI agents to perform autonomous web interactions with persistent state and MCP protocol support, reducing manual intervention in browser-based workfl…
Built from the ground-up for agents, Vessel Browser is an open source AI browser for Linux/Mac/Windows that provides a durable state, MCP control, and BYOK with full autonomous browsing. Use with Hermes Agent, OpenClaw, or connect to your favorite API provider.
- Automate end-to-end web testing workflows without manual browser interaction or setup.
- Build autonomous agents that navigate complex websites and extract data reliably.
- Connect your own API keys to browser automation for custom integration pipelines.
Enables AI agents to perform autonomous web interactions with persistent state and MCP protocol support, reducing manual intervention in browser-based workflows while maintaining control over API credentials and execution environment.
Engineering teams integrating AI agents into testing, automation, or data collection pipelines requiring headless browser control.
https://github.com/unmodeled-tyler/vessel-browser
By unmodeled-tyler
How to Get It
claude plugins install unmodeled-tyler/vessel-browser
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me automate end-to-end web testing workflows without manual browser interaction or setup
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 116 GitHub stars; contributors unknown; last commit 1d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 116 GitHub stars; contributors unknown; last commit 1d ago; license MIT.