I hit this wall last week. I had a long-running session on my workstation. Then I had to leave. And I couldn’t check in from my phone, couldn’t SSH in to see if it finished, couldn’t do anything except wait. So when I found lfg—a web UI control plane for AI coding agents—I spun up a $6 DigitalOcean Droplet and installed it immediately. Here’s what happened.

Quick Verdict

lfg turns any Linux or macOS machine into a private control room for Claude Code, Codex, and OpenCode. One curl | bash install gives you a PWA web UI to launch, monitor, and interact with agent sessions from anywhere. It’s not an agent itself. It’s the infrastructure around the agents you already use. And it solves a real problem that raw tmux and SSH just don’t address well.

The short version: If you run AI coding agents on a remote server, lfg is worth installing right now. It’s 95 stars on GitHub, MIT licensed, and the setup took me under two minutes.

What Is lfg?

lfg (GitHub: BennyKok/lfg) is a lightweight control plane for AI coding agents. Think of it as a web-based mission control for Claude Code, Codex CLI, and OpenCode. You install it on your server, authenticate your agent CLIs, and access everything through a browser or PWA.

Here’s the key distinction: lfg doesn’t replace your agent. It gives you a UI to manage multiple sessions, watch live transcripts, answer prompts remotely, and keep everything running even after you close your laptop. Under the hood it uses tmux for session persistence, so your agents keep working whether the UI is open or not.

I’ve been running it for a few days now. And honestly? It fills a gap I didn’t realize was there until I had it.

If you’ve used tools like Godcoder or oh-my-pi—both of which run agents on your local machine—lfg solves the opposite problem: running them remotely and checking in from anywhere.

Quick Start: Run Claude Code With lfg on a VPS in 5 Minutes

I tested this on a fresh Ubuntu 24.04 Droplet. Here’s exactly what I did:

1. Spin up a VPS — I used a $6/mo DigitalOcean Droplet (2 GB RAM, 1 vCPU, 50 GB SSD). Any Ubuntu or Debian server will work.
2. SSH in and run the installer:

   curl -fsSL https://raw.githubusercontent.com/BennyKok/lfg/main/scripts/setup.sh | bash
   

3. Authenticate your agents — The script installs Node.js and bun, then prompts you to authenticate each CLI.
4. Open the web UI — Visit http://<your-vps-ip>:8766 in your browser.

And that’s it. From SSH login to seeing the web UI took me about 90 seconds of active work. The installer handles dependencies, sets up tmux, and configures auto-restart.

But here’s the part I really like: you don’t need Docker. Unlike most self-hosted tools that require a Docker Compose stack, lfg is a single binary managed by bun. That makes it feel much lighter on a $6 VPS.

lfg Web UI: Managing Agent Sessions From Anywhere

Now the web UI is where lfg shines. It’s a clean, responsive PWA that works in any browser. Here’s what I found after using it for a few days:

Session management — A dashboard shows all running agent sessions. Each one displays status, agent type, and a live transcript stream. You can launch new sessions, kill stuck ones, and reattach to existing ones.

Transcript streaming — Watch agent output in real time. I left a Claude Code session refactoring a codebase overnight, checked in from my phone the next morning, and saw the complete transcript. No SSH needed.

Mobile responsiveness — I tested this from my phone over Tailscale. The UI adapts cleanly to a small screen. I could read transcripts, approve prompts, and even start new sessions.

The killer feature? You can answer Claude Code’s permission prompts from the web UI. So when your agent asks “Can I run this command?” while you’re away, you approve it from your phone.

Three Agent Backends Tested on lfg

I tested lfg with all three supported backends. Here’s how they compare:

Claude Code was the smoothest experience. The CLI authentication is straightforward. And the agent responded well to the tmux session management—I ran a 45-minute refactoring session without any issues.

Codex CLI needed a small extra step: you set the CODEX_API_KEY in your .env file. Still, after that it worked identically. Transcript streaming was fast, and I could see every tool call in real time.

OpenCode was more verbose in the logs, but it worked. I used it for codebase exploration and it handled the flow well.

So all three work. But if you’re only going to run one, start with Claude Code — it’s the most polished integration.

Staying Secure With Tailscale

lfg binds to 127.0.0.1:8766 by default. That means it only listens on localhost — you can’t access it from outside the machine directly. And that’s intentional.

The recommended setup is Tailscale. Install Tailscale on your VPS, connect it to your tailnet, and access the UI via the VPS’s Tailscale IP. No open ports, no reverse proxy, no SSL concerns.

I set this up in about three minutes:

curl -fsSL https://tailscale.com/install.sh | sh
sudo tailscale up

Then opened http://100.x.x.x:8766 from my laptop. And from my phone. And it just worked.

Still, if you prefer a different tunnel (WireGuard, Cloudflare Tunnel, Nginx with Let’s Encrypt), those work too. The key point: don’t expose port 8766 to the public internet. lfg has no built-in auth, so you need network-layer access control.

Deployment Options: Which VPS Fits You?

lfg is lightweight. Even so, any $4–$6/mo VPS will run it comfortably. Here’s what I tested:

I ran lfg on a $6 DO Droplet with zero issues. And RAM usage hovered around 400 MB with one active agent session. CPU was negligible except when the agent was actively retrieving context.

New to DigitalOcean? They offer $200 in free credits—that’s 33 months of lfg hosting. A solid deal if you’re just getting started.

Where lfg Falls Short

I’m a fan of the project. But I’d be lying if I said it’s perfect. Here’s what I noticed:

95 GitHub stars. Now that’s tiny. The project was created in late June 2026, so the community is basically zero right now. If you hit a bug, you’re on your own.

Bun dependency. The runtime relies on bun. Bun is fast, but it’s less battle-tested in server environments. Still, I didn’t run into issues during my testing.

No Docker Compose. There’s a Dockerfile in the repo, but no official docker-compose.yml. For Docker-centric workflows, this adds friction. The developer says it’s coming.

No built-in auth. Security relies entirely on your network layer. Tailscale solves this, but it’s one more thing to set up.

Single-server architecture. lfg runs on one machine. If your VPS goes down, you lose all running sessions. No clustering or failover.

The Bottom Line

lfg is a tool I didn’t know I needed until I tried it. And now I don’t want to go back. The combination of curl | bash simplicity, a clean web UI, and support for all three major agents makes it the most practical way to run AI coding agents on a remote server.

It’s not for everyone. If you’re happy SSHing in and running tmux attach, you might not need it. But if you’ve ever wished you could check on your agent from your phone, or manage multiple sessions without a terminal maze, lfg is worth your time.

I’ll be keeping it running on my Droplet. And I’ll be watching those star counts climb.