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Netclodinho

netclode

Self-hosted coding agent with microVM sandboxes and a native iOS and macOS app.

Netclode iOS App Netclode macOS App

Notes on the fork

This fork exists to make Netclode easier to self-host and operate on a single server. It' being heavilly developped, so expect bugs.

Why this fork exists

  • Simpler deployment: replaces the original Kubernetes+Ansible-oriented deployment path with a Docker Compose workflow that is easier to understand, debug, and maintain.
  • BoxLite-based sandboxes: runs sandboxes with BoxLite in direct Docker/host deployments, avoiding the operational overhead of a full K8scluster.
  • Client compatibility: keeps the control-plane protocol and core behavior aligned so existing upstream-style clients can still work against this fork.

Sandbox security notes

Sandboxing in this fork is based on BoxLite microVMs, with the current tradeoffs documented here:

In short:

  • sandboxes run inside BoxLite VMs (you still need virtualization enabled!)
  • storage is backed by QCOW2 disks
  • pause/continue is currently a VM turn on/off with persistent volume (to be turned into a real snapshop once the Boxlite Go SDK matures)
  • snapshots don't currently work (also TBD when Boxlite Go SDK matures)
  • network isolation is designed for practical self-hosted hygiene, not hostile multi-tenant strong isolation, tailnet isolation currently doesn't work, this could change depending on future Boxlite features

If you are evaluating this fork for production use, read the BoxLite sandbox docs first.

Upstream readme starts from here

Why I built this

I wanted a self-hosted Claude Code environment I can use from my phone, with the UX I actually want. The existing cloud coding agents were a bit underwhelming when I tried them, so I built my own!

I wrote a blog post about how it works: Building a self-hosted cloud coding agent.

What makes it nice

  • Full yolo mode - Docker, root access, install anything. The microVM handles isolation
  • Local inference with Ollama - Run models on your own GPU, nothing leaves your machine
  • Tailnet integration - Preview URLs, port forwarding, access to my infra through Tailscale
  • JuiceFS for storage - Storage offloaded to S3. Paused sessions cost nothing but storage
  • Live terminal access - Drop into the sandbox shell from the app
  • Session history - Auto-snapshots after each turn. Roll back workspace and chat to any previous point
  • GitHub integration - Clone private repos, push commits, create PRs. Per-repo scoped tokens generated on demand via a GitHub App
  • GitHub Bot - @mention on PRs/issues to spin up a sandbox and get a response as a comment. Auto-reviews dependency update PRs from Dependabot/Renovate
  • Multiple SDKs & providers - Claude Code, OpenCode, Copilot, Codex SDKs with Anthropic, OpenAI, Mistral, Ollama, and more
  • Secrets can't be stolen - API keys never enter the sandbox. A proxy injects them on the fly for allowed hosts

How it works

flowchart LR
    subgraph CLIENT["Client"]
        APP["iOS / macOS<br/><sub>SwiftUI</sub>"]
    end

    subgraph VPS["VPS - k3s"]
        TS["Tailscale Ingress<br/><sub>TLS - HTTP/2</sub>"]
        CP["Control Plane<br/><sub>Go</sub>"]
        BOT["GitHub Bot<br/><sub>Go</sub>"]
        REDIS[("Redis<br/><sub>Sessions</sub>")]
        POOL["agent-sandbox<br/><sub>Warm Pool</sub>"]
        JFS[("JuiceFS")]

        subgraph SANDBOX["Sandbox - Kata VM<br/><sub>Cloud Hypervisor</sub>"]
            AGENT["Agent<br/><sub>Claude / OpenCode / Copilot / Codex SDK</sub>"]
            DOCKER["Docker"]
        end
    end

    GH["GitHub Webhooks"]
    S3[("S3")]
    LLM["LLM APIs"]

    APP <-->|"Connect RPC<br/>HTTPS/H2"| TS
    TS <-->|"Connect RPC<br/>h2c"| CP
    GH -->|"Webhooks"| BOT
    BOT <-->|"Connect RPC<br/>h2c"| CP
    CP <-->|"Redis Streams"| REDIS
    CP <-->|"Connect RPC<br/>gRPC/h2c"| AGENT
    POOL -.->|"allocate"| SANDBOX
    JFS <--> SANDBOX
    JFS <-->|"POSIX on S3"| S3
    AGENT --> LLM
Loading

The control plane grabs a pre-booted Kata VM from the warm pool (so it's instant), forwards prompts to the agent SDK inside, and streams responses back. Redis persists events so clients can reconnect without losing anything.

When pausing, the VM is deleted but JuiceFS keeps everything in S3: workspace, installed tools, Docker images, SDK session. Resume mounts the same storage and the conversation continues as if nothing happened. Session metadata such as model selection, SDK type, tailnet access, and custom sandbox resources are also persisted so resumed sessions come back with the same runtime configuration. Dozens of paused sessions cost practically nothing.

Stack

Layer Technology Purpose
Host Linux VPS + Ansible Provisioned via playbooks
Orchestration k3s Lightweight Kubernetes, nice for single-node
Isolation Kata Containers + Cloud Hypervisor MicroVM per agent session
Storage JuiceFS → S3 POSIX filesystem on object storage
State Redis (Streams) Real-time, streaming session state
Network Tailscale Operator VPN to host, ingress, sandbox previews
API Protobuf + Connect RPC Type-safe, gRPC-like, streams
Control Plane Go Session and sandbox orchestration
Agent TypeScript/Node.js SDK runner inside sandbox
GitHub Bot Go Webhook-driven bot for @mentions and dep reviews
Secret Proxy Go Injects API keys outside the sandbox
Local LLM Ollama Optional, local models on GPU
Client SwiftUI (iOS 26) Native iOS/macOS app
CLI Go Debug client for development

Project structure

netclode/
├── clients/
│   ├── ios/              # iOS/Mac app (SwiftUI)
│   └── cli/              # Debug CLI (Go)
├── services/
│   ├── control-plane/    # Session orchestration (Go)
│   ├── agent/            # SDK runner (Node.js)
│   │   └── auth-proxy/   # Adds SA token to requests (Go)
│   ├── github-bot/       # GitHub webhook bot (Go)
│   └── secret-proxy/     # Injects real API keys (Go)
├── proto/                # Protobuf definitions
├── infra/
│   ├── ansible/          # Server provisioning
│   └── k8s/              # Kubernetes manifests
└── docs/

Getting started

See docs/deployment.md for full setup. I tried to make it as easy as possible: ideally a single playbook run.

Quick version:

  1. Provision a VPS with nested virtualization support
  2. Run Ansible playbooks to provision the server
  3. Configure secrets (API keys, S3 credentials, Tailscale OAuth)
  4. Deploy k8s manifests
  5. Connect via Tailscale and you're good to go

Docs

Demo

All videos from the blog post:

Warm pool instant start

No cold start, sandboxes are pre-booted

warm-pool-instant-start.mp4

Session pause & resume

Older sessions are automatically paused to save resources. Resume brings everything back instantly

session-pause-resume.mp4

Local inference with Ollama

Run models on your own GPU

netclode-demo-local-inference-ollama.mp4

CLI shell

Instant sandbox access from the terminal, inspired by sprites.dev

cli-shell-demo.mp4

Git diff view
Diff view with multi-repo support

ios-git-diff-view.mp4
Live terminal
Drop into the sandbox shell from iOS

ios-live-terminal.mp4
Speech input
Speech recognition for prompts

ios-speech-demo.mp4
Tailscale port preview
Expose sandbox ports to the tailnet

tailscale-port-preview.mp4

About

WIP Self hosted cloud coding agents with docker + Boxlite microVMs + tailscale + any harness + a nice iOS app, the lightweight fork of Netclode 🤖

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