lnwjud
Reduces manual workflow overhead for Windows teams by automating cross-domain tasks (Git, process, browser, desktop) through a local AI agent with durable ex…
Windows-first local AI-agent runtime & MCP gateway with 223 configurable tools (217 advertised by default), durable goal continuation, multi-workspace automation, Secure MCP Tunnel, Git/process/WSL/browser/desktop tools.
- Automate repetitive Windows tasks across multiple project workspaces without manual intervention.
- Ask Claude to execute Git commands, run processes, and manage files through a secure local gateway.
- Generate browser automation workflows that continue running toward goals even if interrupted.
Reduces manual workflow overhead for Windows teams by automating cross-domain tasks (Git, process, browser, desktop) through a local AI agent with durable execution and native MCP integration, minimizing external dependencies and compliance risk.
Windows-based engineering teams automating multi-step workflows across development, infrastructure, and desktop environments without cloud vendor lock-in.
https://github.com/engasnm111/lnwjud
By engasnm111
How to Get It
claude plugins install engasnm111/lnwjud
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 repetitive Windows tasks across multiple project workspaces without manual intervention
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): 114 GitHub stars; contributors unknown; last commit 0d 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): 114 GitHub stars; contributors unknown; last commit 0d ago; license MIT.