Sandboxed.Sh is live · pricing from $19/mo · last verified 26 Oct 2026 · viability monitor
Sandboxed.Sh
Orchestrate Claude Code, Codex, Antigravity, OpenCode and Grok from one self-hosted control plane for AI coding agents.
Pick Orb when your agent runs are long, need to happen on hardware you control, and you'd rather approve plan cards from an iPhone than babysit a terminal. Signing into existing Claude, ChatGPT, Grok, Kimi and Antigravity subscriptions through Providers — with CLIProxyAPI holding OAuth refresh — is the detail that saves real money against per-token billing. Budget for the operational load: a Linux backend, containers and upgrades are yours to maintain.
Verdict generatedVerified 5d ago · liveness 47/100 · cite: rightaichoice.com/tools/sandboxed-sh
- Platform teams running long agent missions on code that cannot leave their own servers
- Developers who want one composer for local Mac runs, private Linux nodes and cloud coordinators
- Engineers monitoring multi-hour agent runs from an iPhone instead of a terminal
- Shops reusing Claude, ChatGPT, Grok, Kimi or Antigravity subscriptions instead of per-token API keys
- Teams that will not run or maintain a Linux backend or Docker install
- Users who want a fully managed agent service with zero infrastructure of their own
- Single quick edits that a local Cursor or Claude Code session already handles
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
3 free scans · no card needed
Skip Orb if you are not prepared to run and maintain your own Linux backend or Docker install, or if your work is a quick edit that a local Claude Code or Cursor session already handles without infrastructure.
You pay for the server, domain and any leased sandboxed-node machines yourself — Orb is self-hosted, so infrastructure cost sits outside the product.
Orb's economics depend on how much infrastructure you already run. If you keep one Linux box, converting existing Anthropic, OpenAI, xAI, Kimi or Antigravity subscriptions into shared long-running agent capacity can beat per-token API spend at high volume. Against fully managed agent clouds you are trading operational labor for control of the hardware; against a single local Claude Code or Cursor session the delivery overhead is hard to justify. Budget for the server and containers on top of
In short
Sandboxed.Sh — Orchestrate Claude Code, Codex, Antigravity, OpenCode and Grok from one self-hosted control plane for AI coding agents. Best for Platform teams running long agent missions on code that cannot leave their own servers, Developers who want one composer for local Mac runs, private Linux nodes and cloud coordinators, Engineers monitoring multi-hour agent runs from an iPhone instead of a terminal. Plans from $19/mo.
What is Sandboxed.Sh?
Sandboxed.Sh — Orchestrate Claude Code, Codex, Antigravity, OpenCode and Grok from one self-hosted control plane for AI coding agents. Best for Platform teams running long agent missions on code that cannot leave their own servers, Developers who want one composer for local Mac runs, private Linux nodes and cloud coordinators, Engineers monitoring multi-hour agent runs from an iPhone instead of a terminal. Plans from $19/mo.
Orb — the tool formerly known as sandboxed.sh — is a control plane for AI coding agents that separates where you read and steer an agent from where it actually executes. You connect Anthropic, OpenAI, xAI, Kimi and Google Antigravity subscriptions or API keys in Providers, deploy the Orb Core backend on your own Linux server or via Docker, then launch Claude Code, Codex, Antigravity, OpenCode and Grok from macOS, the web, or iOS. Three execution modes cover the setup spectrum. Placement "client" runs an agent locally on your Mac through Orb's Tauri runner, using your existing CLI logins while mission transcripts sync back to the server. Core or remote_node_id runs work on your own Linux servers and fleet nodes in host directories or isolated systemd-nspawn containers with cgroup resource caps. Cloud agent mode hands durable sessions to Hermes, Grok Bot or Cursor Cloud coordinators and picks them back up inside Orb. Projects hold missions, per-project colors, native skills loaded from skills/<name>/SKILL.md and a bi-directionally synchronized Context folder agents read as @context. Conversations give you collapsible activity and thought folds with nested subagents, /plan mode with question and approval cards, /goal mode for autonomous multi-turn execution, a durable follow-up queue, and a docked /btw side-agent panel for asking questions without interrupting the main turn. Long runs survive via schedule_wakeup durable wake-ups, automatic interrupted-run recovery, and cross-machine mission transfer with SHA-256 verified manifests and Git bundles. A REST API, SSE event stream and unified sandboxed-mcp server expose the same surface to automation. Compared with managed agent platforms, Orb is infrastructure you operate rather than a service you buy — which is the point for teams whose code cannot leave their own hardware. It sits closer to a self-hosted fleet manager than to a single-agent IDE plugin.
Key features
- One composer for Claude Code, Codex, Antigravity, OpenCode, Grok and cloud adapters
- Three execution modes: local Mac via Tauri runner, private Linux nodes, cloud coordinators
- Self-hosted Core backend on Linux or via Docker install
- Isolated systemd-nspawn containers with cgroup resource caps on your own servers
- Host-directory workspaces for agents that need files in place
- Subscription sign-in for Anthropic, OpenAI, xAI, Kimi and Google Antigravity in Providers
- CLIProxyAPI Plus OAuth ownership via SANDBOXED_OAUTH_OWNER=cli-proxy to avoid refresh-token races
- Live provider plan and quota status inspection with model routing
- /plan mode with native question and approval cards
- /goal mode for autonomous multi-turn execution
- Durable follow-up queue that sends on turn completion or immediately
- schedule_wakeup durable mission wake-ups and automatic interrupted-run recovery
- Cross-machine mission transfer with SHA-256 verified file manifests and Git bundles
- Docked /btw side-agent panel for side questions with shared workspace context
- REST API, SSE event stream and unified sandboxed-mcp server for automation
Behind the verdict
The honest framing is that Orb solves a supervision problem, not a model problem. Once a Claude Code or Codex run stretches past an hour, the terminal stops being a good interface — you want foldable activity, subagent visibility, and the ability to fire a follow-up that lands on turn completion rather than mid-stream. That's the gap Orb fills, and the macOS plus iOS clients are where it earns its keep. We'd reach for it when code can't leave your own servers. The systemd-nspawn containers with cgroup caps and host-directory workspaces mean you can run several projects side by side without one runaway agent starving the box. Cross-machine mission transfer with SHA-256 verified manifests is the sort of feature you only appreciate after losing a half-finished run to a node reboot. The subscription passthrough deserves scrutiny in a good way. Routing Anthropic, OpenAI, xAI, Kimi and Google Antigravity accounts you already pay for is cheaper than metered API keys, and letting CLIProxyAPI own refresh tokens with SANDBOXED_OAUTH_OWNER=cli-proxy avoids the refresh-race headaches that bite when several processes share one OAuth session. Where it bites: you are the ops team. Server provisioning, Docker or Linux install, domains, upgrades and container hygiene all land on you. The three execution modes are conceptually clean but you'll need to internalize placement vs. core vs. remote_node_id before your first mission feels natural. Pass if you want a managed agent product with zero infrastructure. A single quick refactor is also not worth the setup — your local Claude Code or Cursor session already covers it. Orb pays off at the multi-hour, multi-repo, multi-machine scale. Closest alternative in spirit is running agents directly on each box over SSH with a shared notes
Models under the hood
as of 2026-10-31
Limitations
- Self-hosting is required: you supply and maintain the Core server (Linux or Docker) rather than signing up for a hosted service.
- Orchestration is split across three execution modes — local Mac via Orb's Tauri runner, private Linux servers/fleet nodes, or cloud coordinators — and that placement split must be understood before configuring agents.
- Execution happens in host directories or isolated systemd-nspawn containers with cgroup resource caps, so provisioning, node health, disk budgets and CLI versions across Core and fleet nodes are yours to track.
- Agent state and mission transcripts sync to your server, making that server a system you must keep alive.
as of 2026-10-09
Researching Sandboxed.Sh? Get your full AI stack in 60 seconds.
Free, no signup — tell us your goal and get tools matched to your budget & existing stack.
Is Sandboxed.Sh still active?
Sandboxed.Sh is live · pricing from $19/mo · last verified 26 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is Sandboxed.Sh? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What do users say about Sandboxed.Sh?
What people actually say about Sandboxed.Sh — is it worth it?
Our community sentiment research written Jul 3, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about Sandboxed.Sh — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 26 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Sandboxed.Sh 12 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed models, pricing page, limitations
- — changed our verdict, integrations, summary, features, pricing tiers, description, who should skip it
- — changed SSL certificate
- — changed who should skip it, our verdict, setup time, pricing fit, use cases, features, description, hidden costs, integrations, limitations, summary, switching in, who it suits, switching out, models, pricing tiers
- — changed models, platforms, pricing page, limitations
- — changed use cases, who it suits, description, our verdict, features, hidden costs, limitations, switching in, switching out, who should skip it, pricing fit, setup time, summary
Showing the 6 most recent of 12 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Sandboxed.Sh cost in 2026?
Sandboxed.Sh: Plans from $19/mo. Pricing last verified 26 Oct 2026.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Sandboxed.Sh's pricing actually pencils out — and where peers do it cheaper.
Orb's economics depend on how much infrastructure you already run. If you keep one Linux box, converting existing Anthropic, OpenAI, xAI, Kimi or Antigravity subscriptions into shared long-running agent capacity can beat per-token API spend at high volume. Against fully managed agent clouds you are trading operational labor for control of the hardware; against a single local Claude Code or Cursor session the delivery overhead is hard to justify. Budget for the server and containers on top of
Has Sandboxed.Sh's pricing changed?
No plan price for Sandboxed.Sh has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Sandboxed.Sh?
Pick Sandboxed.Sh if you are Platform teams running long agent missions on code that cannot leave their own servers, Developers who want one composer for local Mac runs, private Linux nodes and cloud coordinators, Engineers monitoring multi-hour agent runs from an iPhone instead of a terminal, Shops reusing Claude, ChatGPT, Grok, Kimi or Antigravity subscriptions instead of per-token API keys.
Look elsewhere if you are Teams that will not run or maintain a Linux backend or Docker install, Users who want a fully managed agent service with zero infrastructure of their own, Single quick edits that a local Cursor or Claude Code session already handles, Anyone unwilling to learn the three execution modes and container model.
Skip it if Skip Orb if you are not prepared to run and maintain your own Linux backend or Docker install, or if your work is a quick edit that a local Claude Code or Cursor session already handles without infrastructure.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Sandboxed.Sh actually fits — and what changes day-one when you adopt it.
Deploy the Orb backend on an internal Linux server with Docker, connect Anthropic and OpenAI subscriptions in Providers, create a project with a skills/<name>/SKILL.md standards file, then launch a Claude Code mission against a legacy module in an isolated systemd-nspawn container with cgroup caps.
Outcome: The refactor runs on your own hardware with resource limits, transcripts synced to your server, and the diff reviewable the next morning without any code leaving the network.
Start a mission on the Mac through the Tauri runner using existing CLI logins, then leave the desk and follow the live run in the iOS app — collapsing tool folds, reading thinking, and sending follow-ups from the shared Markdown context.
Outcome: Multi-hour runs keep moving while you are away, and you can answer a /plan approval card or redirect the agent without opening a terminal.
Create missions over POST /api/control/missions with backend and placement set per job, subscribe to /api/control/stream for tool_call and text_delta events, and drive operations through the sandboxed-mcp operator profile with idempotency keys.
Outcome: Agent runs become a programmable service inside your own stack, with durable action receipts and scoped one-hour session tokens instead of shared long-lived credentials.
Use cases
- Run an overnight refactor mission on your own Linux node and review the diff from the macOS client in the morning.
- Point an agent at a GitHub issue and let /goal mode work across turns until a PR is ready.
- Enforce team coding standards through a shared skills repository (skills/<name>/SKILL.md) the agent follows across projects.
- Run agents against healthcare or finance code knowing execution stays in your own systemd-nspawn containers with cgroup caps.
- Keep multiple projects with different toolchains and rules in isolated container workspaces with per-project colors.
- Stream live thinking and tool calls from the iOS app instead of staying at your desk.
- Move an in-flight mission to another machine with a SHA-256 verified manifest and Git bundle instead of restarting.
- Let internal tooling create and steer missions via the REST API and subscribe to the SSE event stream.
Setup time & first value
How long it actually takes to get something useful out of Sandboxed.Sh — broken out by persona, not the marketing-page minute.
Assume an afternoon for the platform engineer: deploy the backend on Linux or via Docker, then configure providers and the first machine. A developer reusing an existing Mac CLI login gets to a first mission quickly through Orb Desktop, but learning the three execution modes takes longer. Expect realistic evaluation time for teams that need to verify container and fleet behavior before trusting
Switching to or from Sandboxed.Sh
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a bare Claude Code CLI on a Linux box: deploy the Orb Core backend, sign in the same Anthropic subscription in Providers, and re-create the workflow as a project with a skills directory.
- →From local-only Claude Code or Cursor sessions on your Mac: install Orb Desktop, point it at your server, and keep running locally via the Tauri runner while transcripts start syncing.
- →From ad-hoc tmux and SSH agent sessions: replace them with durable missions that survive disconnects and recover automatically when a run is interrupted.
- →From per-token API billing: sign in supported subscription accounts in Providers, or route OAuth through CLIProxyAPI Plus with SANDBOXED_OAUTH_OWNER=cli-proxy.
- →From single-machine automation scripts: move them onto the REST API and SSE stream so mission creation and steering are programmatic.
- ↗To a fully managed agent cloud: export mission transcripts and the Context folder, then re-create the projects on a hosted service that runs the infrastructure for you.
- ↗To a local-only Claude Code or Cursor setup: copy the Context folder and skills directory into the repo and drop the self-hosted backend.
- ↗To a single-project workflow: keep one workspace directory, then stop running the Core server and fleet nodes you no longer need.
- ↗To a CI-native agent pipeline: move durable follow-up and schedule_wakeup logic into your CI scheduler and call agent CLIs directly.
Integrations
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Sandboxed.Sh”, and we withheld 6: 6 could not be judged, because “Sandboxed.Sh” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Sandboxed.Sh.
Official links
What are the best Sandboxed.Sh alternatives?
The closest alternatives to Sandboxed.Sh we list are Paseo, Vicoa and Replicas. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Paseo | Free | Free | — |
| Vicoa | Freemium | Pricing not published | — |
| Replicas | Freemium | Pricing not published | — |
Alternatives to Sandboxed.Sh
View all
Paseo
Paseo is a self-hosted control plane for orchestrating Claude Code, Codex, Copilot and 30+ coding agents from desktop, phone or browser.
Tools that pair well with Sandboxed.Sh
Common stack mates teams adopt alongside Sandboxed.Sh, with the specific reason each pairing earns its keep.
Paseo
Paseo is a self-hosted control plane for orchestrating Claude Code, Codex, Copilot and 30+ coding agents from desktop, phone or browser.
Vicoa
Vicoa is a remote control plane for coding agents: run Claude Code, Codex, and dozens more on your own machines, then steer any session from your phone.
Replicas
Replicas runs Claude Code, Codex, Cursor, and OpenCode coding agents in isolated cloud VMs and hands back pull requests.
Sandboxed.Sh vs its closest rival
Sandboxed.Sh's closest head-to-head is with Spider Cloud — Choose Sandboxed.Sh if you need secure, long-running AI coding agents that operate on your own infrastructure—ideal for sensitive codebases and multi-hour refactors. Choose Spider Cloud if your AI agents require fast, reliable web data extraction at scale, with recent additions like Browser AI commands and a scraper catalog making it even more powerful for RAG pipelines. They solve fundamentally different problems, so your choice depends on whether you need to orchestrate code agents or feed your AI with live web data. Verdict generated
Head-to-head comparisons
Sandboxed Sh vs Spider Cloud
Choose Sandboxed.Sh if you need secure, long-running AI coding agents that operate on your own infrastructure—ideal for sensitive codebases and multi-hour refactors. Choose Spider Cloud if your AI agents require fast, reliable web data extraction at scale, with recent additions like Browser AI commands and a scraper catalog making it even more powerful for RAG pipelines. They solve fundamentally different problems, so your choice depends on whether you need to orchestrate code agents or feed your AI with live web data.
GeneratedSandboxed Sh vs Voyage Ai
Choose Voyage AI if your priority is accuracy and low-cost vector storage for enterprise RAG on finance, legal, or code. Choose Sandboxed.Sh if you need a self-hosted orchestrator to run AI coding agents for hours without session limits, keeping sensitive code on-premises.
GeneratedSandboxed Sh vs Temporal Ai
Temporal AI is the better choice for teams needing a robust, scalable durable execution platform that integrates deeply with AI agent frameworks and supports complex multi-step workflows with automatic recovery. Sandboxed.sh is ideal for security-conscious developers running long coding agent sessions on their own infrastructure, but lacks the broad orchestration features and managed scalability of Temporal.
GeneratedPieces For Developers vs Sandboxed Sh
If you need to run unattended AI agents for hours on sensitive code, Sandboxed.Sh is the only choice—it’s self-hosted and containerized. If you lose context daily across apps and want automatic recall, Pieces for Developers gives you a searchable timeline without manual effort. They solve opposite problems: one is an agent orchestrator, the other a memory recorder.
GeneratedFrequently asked questions
Used Sandboxed.Sh? Help shape our editorial sentiment research.