Containarium
Open-source agent runtime giving each AI agent a persistent, network-isolated Linux box on Kubernetes or LXC, reachable over SSH with a built-in MCP server.
Adopt Containarium if you run long-lived coding agents or CI jobs you actually need to debug, and you want the environment inside your own infrastructure rather than a vendor's black box. The keep-on-failure box is the most useful thing here: an hour of live SSH into a broken test run beats any dashboard. It is honest about its edges — v0.x CLI, Linux-only, PR previews explicitly roadmap and not shipping, and you bring the agent — so budget for adopting a primitive rather than a product. Where E2B and Modal sell managed sandbox APIs, Containarium's bet is MCP-native boxes that persist between sessions.
Verified 4d ago · liveness 76/100 · cite: rightaichoice.com/tools/containarium
- Developers running long-lived coding agents that need a box surviving across sessions
- Teams whose CI failures need live SSH debugging instead of a dead black-box runner
- Agent fleet operators assigning one box per task, per user, or per tenant
- Platform engineers building custom MCP tools that need a real Linux environment
- Anyone wanting a no-code agent builder — Containarium is a primitive and you bring the agent
- Non-Linux stacks: there is no Windows or macOS agent runtime
- Teams that want a fully managed sandbox API with nothing to operate, better served by E2B or Modal
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Skip Containarium if you want a fully managed sandbox API with nothing to operate, need Windows or macOS agent runtimes, or plan to rely on PR preview URLs — those are explicitly roadmap, not shipping.
Self-hosting the OSS tier costs nothing in license fees but requires an Ubuntu VM and the Kubernetes or LXC operational time to run it yourself
Containarium's OSS tier is Apache 2.0 at $0 and runs on one Ubuntu VM, which puts the entry point below managed sandbox API vendors like E2B and Modal in cash outlay but above them in operational effort. The cloud control plane carries a usage-based paid tier on top of a free level, and the enterprise tier is contact-sales with self-hosted runners, audit log, SSO, and data residency. Pick OSS if you have platform engineers; pick the hosted control plane if you do not.
In short
Containarium — Open-source agent runtime giving each AI agent a persistent, network-isolated Linux box on Kubernetes or LXC, reachable over SSH with a built-in MCP server. Best for Developers running long-lived coding agents that need a box surviving across sessions, Teams whose CI failures need live SSH debugging instead of a dead black-box runner, Agent fleet operators assigning one box per task, per user, or per tenant. Free to use.
What's new in Containarium
Checked 4 days agoAcross the latest 1 update: 1 news mention.
What people actually say about Containarium — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
14 mentions across 1 source (Hacker News) · researched Jul 3, 2026.
Average across the 1 source that answered — each source counts once, not each post.
- +SSH-native isolation prevents API token leaks to agents.
- +eBPF egress policy enforces fine-grained network sandboxing.
- +Quick provisioning — seconds per environment on LXC.
- +MCP-native CLI integrates easily with Claude Code and Cursor.
- +Persistent hostname with TLS simplifies agent connectivity.
- −Very early-stage with limited community and documentation.
- −Competes with mature tools like Incus and Proxmox.
- −Security model depends on runtime, raising doubts.
- −Scalability beyond 100 containers per VM unproven.
- −No native integrations with major CI/CD platforms.
- • Self-hosting requires Kubernetes or LXC infrastructure.
- • Cloud pricing and limits not publicly documented.
Viability Score
How well maintained and how widely used is Containarium? 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 →Key Features
- Persistent, network-isolated Linux box per AI agent
- SSH-native isolation with a routable hostname and TLS
- eBPF egress policy sandboxing host, control plane, and other tenants
- Runs boxes as LXC containers or Kubernetes pods
- Built-in MCP server exposing shell and file operations over stdio
- Drive Claude Code, Cursor, Cline, OpenCode, or your own agent over MCP
- One-command box creation with contarium create
- Sentinel using sshpiper, Caddy, and PROXY protocol for routing and TLS
- Ephemeral CI box per GitHub Actions job with warm caches across runs
- keep-on-failure holds a failed box alive for an hour of live SSH debugging
- footprintai/containarium-run@v1 GitHub Action
- Three-field .github/containarium.yml for image, setup, and test
- Drop custom MCP servers beside the built-in one
- No kube-apiserver token exposed to agent boxes
- Local web UI for managing and listing boxes
About Containarium
Containarium is an Apache 2.0 open-source runtime that gives each AI agent its own isolated Linux box instead of a shared laptop or an opaque CI runner. You bring the agent — Claude Code, Cursor, Cline, OpenCode, or one you wrote — and Containarium supplies the environment it acts in: real root, a real filesystem, and eBPF egress policy enforced against your host, the cluster control plane, and every other tenant. Boxes run as LXC containers or Kubernetes pods, so you are not handing an autonomous agent a kube-apiserver token. Each box gets a routable hostname with TLS from a built-in sentinel (sshpiper + Caddy + PROXY protocol), so SSH and HTTP work without extra plumbing. Inside the box an MCP server exposes shell and file operations over stdio, so any MCP-aware agent drives it over SSH or HTTPS by hostname with no glue code. Setup is one command, `containarium create`, which spins up the container and registers the route on the sentinel. The second surface is CI: the footprintai/containarium-run@v1 GitHub Action creates an ephemeral box per job with warm caches across runs, and keep-on-failure holds a failed box alive for an hour so a human or an agent can SSH into the broken state in place. Wiring comes in tiers — hosted cloud tryout, self-hosted runners, an audited tier with SSO and data-residency documentation, and an air-gapped offline bundle. The same primitive doubles as a consolidation layer for cloud VMs: many isolated containers on machines you already pay for, with RBAC, audit log, SSO, security scanning, and backups.
Behind the Verdict
The interesting thing about Containarium is what it refuses to be. Most agent tooling in 2026 tries to own the agent loop, or the model, or the orchestration layer. Containarium owns none of those. It owns the box: one Linux environment per agent, exposed on a hostname, with an MCP server inside it. That framing is unusually clear-headed, and it maps onto a real problem — agents that edit files and run shell commands need somewhere to do it that is not your laptop and not a shared runner. The security story is the strongest part. Boxes run as LXC containers or Kubernetes pods, the agent never receives a kube-apiserver token, and eBPF egress policy is enforced against the host, the cluster control plane, and every other tenant. The sentinel built on sshpiper, Caddy, and PROXY protocol means each box gets a routable hostname with TLS without you writing ingress config. For MCP-native work this is a genuine shortcut: point Claude Code, Cursor, or Cline at the box's MCP endpoint and it can drive shell and file operations with no glue code, and you can drop a custom MCP server beside the built-in one so every connected agent sees both. The CI path is the part most teams will feel first. The footprintai/containarium-run@v1 Action spins an ephemeral box per job with warm caches across runs, and keep-on-failure holds a failed box alive for an hour so you can SSH in or hand it to an agent to debug in place. That directly attacks the worst thing about hosted runners: the state vanishes exactly when you need it. The .github/containarium.yml config is three fields — image, setup, test — and the homepage's own instruction is to resist adding a fourth, which is a good sign about scope discipline. The weaknesses are stated by the vendor rather than discovered by you, which is worth something. The OSS CLI is v0.x, so interfaces can still shift under a production dependency. It is Linux-only; there is no Windows or macOS agent runtime. PR preview URLs, where every pull request gets a live URL, are described on the homepage as planned and explicitly not shipping yet — what ships today is the layer underneath. Self-hosting means operating Kubernetes or LXC yourself, which is a real skills assumption, not a checkbox. And the tool is a primitive: anyone expecting a no-code agent builder is in the wrong place. Compared with E2B and Modal, which sell managed sandbox APIs you consume and never operate, Containarium trades convenience for control and for keeping code and artifacts inside your network. If your constraint is 'the agent cannot touch the cluster control plane and the artifacts cannot leave the perimeter,' that trade is the whole point. The recent write-up on running five agents on five Linux boxes describes exactly the shape this is built for: parallel agents, one box each, plus a quality process the agents follow — the tool supplies isolation and routing, and you supply the process.
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Real-world workflow fit
Concrete scenarios for the personas Containarium actually fits — and what changes day-one when you adopt it.
You run `containarium create` to spin up an LXC box, point Claude Code at the box's MCP server over SSH, and let it edit files and run commands across sessions.
Outcome: The agent works in an isolated environment with a routable hostname and TLS, and its state survives between sessions instead of dying with your terminal.
You add footprintai/containarium-run@v1 to your workflow with keep-on-failure: true and a three-field .github/containarium.yml specifying image, setup, and test.
Outcome: A failing job posts the trace on the PR and holds the box alive for 58 minutes, so you SSH in or hand it to an agent to debug the broken state in place.
You assign one box per task, per user, or per tenant and let the built-in sentinel route hostnames, while a custom MCP server sits beside the built-in one.
Outcome: Each agent gets its own isolated filesystem and egress policy, with no kube-apiserver token exposed and no shared credentials between tenants.
Use Cases
- Give Claude Code or Cursor a persistent box that survives across sessions for long-running projects
- Spin a box per PR, run the agent or test suite inside it, and throw it away — no racing the runner
- Keep a failed CI box alive for an hour and SSH in or hand it to an agent to debug in place
- Assign one box per task, per user, or per tenant and let the sentinel handle routing
- Drop a custom MCP server beside the built-in one so every connected agent sees both
- Run untrusted agent workloads under SSH-native isolation without exposing cluster tokens
- Consolidate cloud VMs into many isolated containers on machines you already pay for
- Give a deploy bot its own box and dedicated hostname instead of shared credentials
Limitations
- Containarium is an agent runtime that supplies isolated Linux environments for AI agents.
- It does not include its own AI model; it works with external agents such as Claude Code, Cursor, Cline, OpenCode, or custom agents connecting via MCP, SSH, or HTTPS.
- The open-source CLI is at v0.x, so interfaces can still shift.
- The product is Linux-only — there is no Windows or macOS agent runtime.
- PR previews, where every pull request gets a live URL, are described on the homepage as planned and explicitly not shipping yet; what ships today is the layer underneath, the CI runner that reads .github/containarium.yml and can keep a box alive after a failure.
- Consolidating cloud VMs into containers per host means running the container platform yourself, and the self-hosted path assumes you are comfortable operating Kubernetes or LXC.
as of 2026-10-15
Verification history
We have re-verified Containarium 8 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.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
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.
Plans compared
For each published Containarium tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Containarium OSS
$0
Ideal for
Platform-savvy developers and small teams with an Ubuntu VM who want the full primitive without a hosted dependency
What this tier adds
Starting tier — Apache 2.0 self-hosted, includes the CLI (create / list / route / expose-port), the sentinel for hostnames and TLS, the built-in MCP server, and a local web UI
Containarium Cloud — Free
$0/mo
Ideal for
Evaluators and hobby open-source projects that want a box running in about five minutes without operating anything
What this tier adds
Adds a hosted control plane on top of the OSS primitive, plus the containarium-run@v1 GitHub Action with per-job ephemeral boxes and warm caches
Containarium Cloud — Paid
Usage-based
Ideal for
Teams that want boxes on demand without running the control plane themselves
What this tier adds
Adds a hosted control plane that runs for you, so you create and manage boxes without operating the platform, with MCP-driven agent boxes on demand
Enterprise
Contact sales
Ideal for
Enterprises and regulated teams whose code, tests, and artifacts cannot cross to vendor infrastructure
What this tier adds
Adds self-hosted runners, audit log, SSO, data-residency documentation, an air-gapped offline install bundle with a private Git server, BYOC sovereign boxes, RBAC, security scanning, and backups
Where the pricing makes sense
The company stage and team size where Containarium's pricing actually pencils out — and where peers do it cheaper.
Containarium's OSS tier is Apache 2.0 at $0 and runs on one Ubuntu VM, which puts the entry point below managed sandbox API vendors like E2B and Modal in cash outlay but above them in operational effort. The cloud control plane carries a usage-based paid tier on top of a free level, and the enterprise tier is contact-sales with self-hosted runners, audit log, SSO, and data residency. Pick OSS if you have platform engineers; pick the hosted control plane if you do not.
Setup time & first value
How long it actually takes to get something useful out of Containarium — broken out by persona, not the marketing-page minute.
On the hosted cloud path the homepage quotes roughly five minutes for the Tier 0 tryout: sign up, use the containarium-run Action, and a box is running. Self-hosted Tier 1 is quoted at about 30 minutes for the OSS install plus the runner kit for N ephemeral runners. Enterprise and air-gapped tiers add SSO, audit log, data residency, or offline bundle work on top of that.
Switching to or from Containarium
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a shared development laptop: create a box per agent and connect Claude Code or Cursor over MCP, keeping agent file edits off your machine
- →From GitHub-hosted runners: swap in footprintai/containarium-run@v1 with a three-field .github/containarium.yml and gain warm caches plus keep-on-failure debugging
- →From a black-box CI runner: run the same test command inside a box and SSH into the kept-alive failure state instead of reading logs after teardown
- →From scattered cloud VMs: consolidate them into isolated LXC containers or Kubernetes pods on machines you already pay for
- ↗To E2B or Modal: move to a managed sandbox API if you want to stop operating the container platform yourself
- ↗To a no-code agent builder: move out if you want the agent itself, not just the box, supplied by the vendor
- ↗To standard Kubernetes tooling: keep the pods and drop Containarium if you no longer need the sentinel routing and MCP server layer
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Containarium”, and we withheld 6: 6 could not be judged, because “Containarium” 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 Containarium.
Official links
Tools that pair well with Containarium
Common stack mates teams adopt alongside Containarium, with the specific reason each pairing earns its keep.
Phidata
Agno (formerly Phidata) is an open-source Python agent SDK plus AgentOS, a runtime that serves agents as an API and an MCP server in your
VCPToolBox
Open-source backend runtime that gives LLMs persistent memory, hot-swappable plugins and multi-agent coordination via the VCP protocol.
StereOS
Open-source Linux OS that runs AI coding agents inside disposable, fully isolated VMs.
Featured Head-to-Head Comparisons
Containarium vs Spider Cloud
Choose Containarium if you need to run coding agents (like Claude Code) in isolated, SSH-accessible Linux environments with GPU support. Choose Spider Cloud if your priority is fast, cheap web scraping for AI agents and RAG pipelines. They serve fundamentally different needs, so pick based on whether you need an agent runtime or web data extraction.
Containarium vs Temporal Ai
Temporal AI is the clear winner for teams needing robust workflow orchestration with automatic retries and durability, especially for AI agents and microservices. Containarium excels if your primary need is a secure, isolated Linux box for coding agents like Claude Code—but its scope is narrower. Choose Temporal for broad orchestration; pick Containarium for agent sandboxing.
Containarium vs Presto Voice
Presto Voice and Containarium serve completely different buyers. Presto Voice is purpose-built for QSR chains needing a proven drive-thru voice AI solution with upselling, while Containarium is an open-source infrastructure tool for developers running coding agents in isolated environments. Your choice depends entirely on your domain: restaurant ops or agent engineering. There is no overlap.
Alternatives to Containarium
View all
Phidata
Agno (formerly Phidata) is an open-source Python agent SDK plus AgentOS, a runtime that serves agents as an API and an MCP server in your
VCPToolBox
Open-source backend runtime that gives LLMs persistent memory, hot-swappable plugins and multi-agent coordination via the VCP protocol.
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