Open-source alternatives to E2B: 5 code sandbox for AI agents tools compared
Replacing E2B means every command an agent runs stops crossing the network to a vendor's machines and starts crossing it to hardware you own, so the isolation question and the latency question move together. Most readers should start with opensandbox-group/OpenSandbox, the one candidate here that answers a create request with either a local Docker runtime or a Kubernetes cluster.
What E2B does, and why people look elsewhere
E2B is a hosted sandbox that gives an AI agent somewhere to run code: each session is an isolated virtual machine that starts in seconds and is thrown away afterwards.
- the code an agent writes and runs is executed on the vendor's machines
- every command crosses the network to the vendor's sandbox, which changes how long a step takes
- there is no self-hosted edition of the same managed sandbox, so the environment is the vendor's to change
The candidates at a glance
| Project | Licence | Maintenance | Language | GitHub stars | Install |
|---|---|---|---|---|---|
| opensandbox-group/OpenSandbox | Apache-2.0Permissive: commercial use allowed | Commits in the last six monthsLast push October 21, 2026 | Python | 16,028 | See analysis |
| superradcompany/microsandbox | Apache-2.0Permissive: commercial use allowed | Commits in the last six monthsLast push October 21, 2026 | Rust | 8,757 | Command documented |
| anthropics/sandbox-runtime | Apache-2.0Permissive: commercial use allowed | Commits in the last dayLast push October 22, 2026 | TypeScript | 5,637 | Command documented |
| kubernetes-sigs/agent-sandbox | Apache-2.0Permissive: commercial use allowed | Commits in the last six monthsLast push October 21, 2026 | Go | 4,344 | See analysis |
| agent-infra/sandbox | Apache-2.0Permissive: commercial use allowed | Commits in the last six monthsLast push September 14, 2026 | Python | 6,064 | See analysis |
Each alternative in detail
opensandbox-group/OpenSandboxSecure, Fast, and Extensible Sandbox runtime for AI agents. Sandbox Runtime: Built-in lifecycle management supporting Docker and high-performance Kubernetes runtime, enabling both local runs and large-scale distributed scheduling.
- Best for
- You are running untrusted model-generated code and want one control plane that works on a laptop with Docker and on a cluster with Kubernetes, with a credential vault and per-sandbox egress policy around the workloads.
- What you give up
- The Python SDK is on a 0.1 development line while the server sits on 1.1, so you are pairing an immature client with a moving server, and our analysis of OpenSandbox tells you to pin the SDK deliberately. The published creation latency is conditional, because the README states in a footnote that template artifacts must be cached, on a reference host, over repeated creates, and our analysis adds that cold starts have to be budgeted for because image pulling is not part of that figure.
superradcompany/microsandbox🧱 easy fast local-first microVM runtime and library
- Best for
- You want untrusted code to run in a hardware-isolated microVM on your own machine, with no server to operate and no daemon that outlives the process which started the sandbox.
- What you give up
- The README says the project is still beta software with breaking changes, missing features and rough edges to expect, and our analysis of Microsandbox tells you to pin a version that moves weekly. There is no daemon, so a sandbox dies with the process that created it, and nothing fails at install time when the host lacks KVM or WHP, so the hardware check has to happen first. Secret injection is a host-side feature of its own API rather than something baked into an image, so an agent that needs a credential has to be created through that API.
- First install step
- Full setup guide
npm i microsandbox cargo add microsandbox uv add microsandbox go get github.com/superradcompany/microsandbox/sdk/go
anthropics/sandbox-runtimeA lightweight sandboxing tool for enforcing filesystem and network restrictions on arbitrary processes at the OS level, without requiring a container.
- Best for
- You run agents, MCP servers or shell commands you do not fully trust and want filesystem and network restrictions enforced by the operating system, with no container runtime in the picture at all.
- What you give up
- The README calls it a beta research preview and warns that the APIs and configuration formats may evolve, so our analysis of srt says to skip it if you need a stable configuration contract in production. There is also no session lifecycle here: you run a process under restrictions, but there is no create-and-discard model for an agent loop. Our analysis asks you to check that the settings file parses the way you intend, because an empty allowWrite or allowedDomains list means no access rather than full access.
- First install step
- Full setup guide
npm install -g @anthropic-ai/sandbox-runtime
kubernetes-sigs/agent-sandboxagent-sandbox enables easy management of isolated, stateful, singleton workloads, ideal for use cases like AI agent runtimes and reinforcement learning (RL).
- Best for
- You already run Kubernetes and need one long-lived, stateful pod per agent or reinforcement learning environment, with a stable hostname and optional persistent storage.
- What you give up
- It is an orchestrator and not an isolation layer, so the README says it delegates low-level container isolation to runtimes such as gVisor or Kata Containers through a RuntimeClass, and our analysis of agent-sandbox tells you not to adopt it expecting that isolation itself. There is also no session that starts fast and is thrown away, which is the shape an agent loop usually wants, and the install is a manifest you have to pin to a release tag and check against a previous install.
agent-infra/sandboxAll-in-One Sandbox for AI Agents that combines Browser, Shell, File, MCP and VSCode Server in a single Docker container.
- Best for
- You want an agent to have a browser, a shell, a file API, a code server and MCP servers inside one container, so that a file downloaded in the browser can be read from the terminal in the same session.
- What you give up
- Everything runs in one container, so there is no per-tool isolation, and our analysis of the AIO sandbox says to skip it if your threat model requires that. The quick start runs the container with seccomp unconfined, so a hardened host may refuse to start it, and our analysis tells you to verify that the API key actually gates the endpoints you expose and that the port stays private behind a reverse proxy. The services stay open when no key is set, which is the backward-compatible default.
Five sandboxes, five isolation models: a platform, a microVM, an OS policy, a pod, one image
E2B is a hosted sandbox that gives an AI agent somewhere to run code. Each session is an isolated virtual machine that starts in seconds and is thrown away afterwards. The reasons teams look elsewhere are about where the work happens and who controls it: the code an agent writes and runs is executed on the vendor's machines, every command crosses the network to the vendor's sandbox, which changes how long a step takes, and there is no self-hosted edition of the same managed sandbox, so the environment is the vendor's to change.
The five candidates answer that with five different isolation models, and that is the axis worth comparing on.
opensandbox-group/OpenSandbox is a platform with a lifecycle API. The README describes SDKs for several languages, a terminal CLI, an MCP server, and a sandbox protocol with published API specs so you can plug in a custom runtime. Its runtimes are Docker locally and Kubernetes for large-scale distributed scheduling, and its environments include command execution, a filesystem and a code interpreter, with examples for coding agents, browser automation and desktops. Two features make it defensible for untrusted code: a credential vault that injects secrets into outbound requests without handing the real secret to the workload, and per-sandbox egress controls.
superradcompany/microsandbox is a microVM runtime. The README describes booting a microVM as a child process of your own program, with OCI images, a Docker-like workflow, a CLI, SDKs for several languages, and fork plus snapshot support. It makes two claims that matter for an agent: average boot times under 100 milliseconds, and secret keys that never enter the virtual machine. There is no setup server and no long-running daemon.
anthropics/sandbox-runtime is not a sandbox in the virtual machine sense. It wraps a process in restrictions enforced by the operating system: Seatbelt profiles on macOS, bubblewrap on Linux, and a dedicated local account with a Windows Filtering Platform egress fence on Windows. The README is explicit that this is a beta research preview built for Claude Code and that the configuration formats may still move.
kubernetes-sigs/agent-sandbox is a control plane for Kubernetes and nothing more. Its README says so in a note: it is a sandbox orchestrator that delegates low-level container isolation to runtimes such as gVisor or Kata Containers through a RuntimeClass. What it adds is a Sandbox custom resource for one stateful pod with a stable identity, plus templates, claims and warm pools.
agent-infra/sandbox puts everything in one container: a browser, a terminal, a file API, MCP servers and a code server in a single image, so an agent can act on one filesystem.
Who was left out, and why the other hosted sandboxes are not here
Two groups are absent, and the reasons are worth stating.
The first is the other hosted sandboxes. They run the agent's code on infrastructure the vendor owns, which is the property you are removing. E2B itself is in this group, and the reader who keeps it keeps a good product.
The second is the general-purpose container and virtualisation tooling: Docker, Podman, Firecracker, gVisor and Kata Containers on their own. They are the building blocks, and several of the candidates here are thin layers over them. On their own they give you a process boundary but not a session lifecycle for an agent, which is the part an agent loop needs: create, run, collect output, throw away.
One omission is specific. None of the five is a managed service in the shape E2B has, which is exactly the gap E2B leaves. What you get instead is the layer underneath, with the scheduling, the uptime and the patching in your hands.
Choosing by scenario: one developer, a small team, a company with compliance needs, a developer embedding a sandbox in an agent loop
A solo developer running an agent loop on a laptop should look at superradcompany/microsandbox. The README describes an embeddable design with no setup server and no long-running daemon, so the sandbox is a child process of the program that starts it, and it works on Apple Silicon, on a Linux host with KVM enabled and on Windows with WHP. Our analysis of Microsandbox says that is the right shape when you need to run code you would rather not trust and can tolerate pinning a version that moves. The same analysis warns that nothing fails at install time when the host lacks KVM or WHP, so check that first.
A small team that needs one sandbox per agent session, with several tools inside it, should look at agent-infra/sandbox. The README shows a single image carrying a browser, a terminal, a file API, a code server, a notebook server and MCP servers, and the quick start is one container run. Our analysis of the AIO sandbox says it fits when you want an agent to download a file in the browser and then read it from the shell, and when one trusted container per session is acceptable.
A company with compliance needs has to fix the isolation boundary before it picks the tooling. anthropics/sandbox-runtime enforces policy at the operating system level with no container runtime, a small footprint and a narrow threat model, but our analysis of srt says to skip it if you need a stable configuration contract in production. opensandbox-group/OpenSandbox and kubernetes-sigs/agent-sandbox suit teams that already run Kubernetes and want a control plane around it.
A developer embedding a sandbox in an agent loop should match the tool to what the agent actually does. For model-generated code, the code interpreter environment in OpenSandbox and its Firecracker option come closest to a hosted session. For a plugin or a local script, the microVM in microsandbox is closer. For an MCP server that should not be able to read your filesystem, srt is the smallest thing that works, and the README shows it wrapping an MCP server from a configuration file.
What running the sandbox yourself costs: a hypervisor, a cluster, or a container runtime
Running the sandbox is the bill, and it differs sharply between the five.
superradcompany/microsandbox needs a hypervisor and nothing else. The README lists Apple Silicon on macOS, KVM enabled on Linux and WHP enabled on Windows as the requirements, and it warns that the project is still beta software with breaking changes and rough edges to expect. There is no server to run and no database to back up, which is the whole appeal. The cost is the host.
anthropics/sandbox-runtime also needs no server. It needs the native primitives for your platform, and the README explains that traffic goes through proxy servers on the host, with the Linux path removing the network namespace entirely and the macOS path allowing communication only to a specific localhost port. The configuration is a settings file in your home directory, and our analysis of srt tells you to check that your allowlist blocks what you expect, because an empty allowWrite list means no write access rather than full access.
opensandbox-group/OpenSandbox needs a container runtime or a cluster. Its local path is a configuration file and a server start, with Docker required and Python 3.10 or later for the examples, and its Kubernetes runtime is the production shape. The README also says release images are signed keylessly and carry provenance attestations, and that you should pin production images by digest.
kubernetes-sigs/agent-sandbox needs the cluster it lives in, and the resource that runs inside it. The install is a single manifest applied with kubectl, and the verification step checks both the custom resource definition and the controller deployment. The RuntimeClass you choose is where the isolation actually comes from.
agent-infra/sandbox needs the least. One container, one port bound to the loopback address, and one environment variable for the API key. The cost is the seccomp setting, since the README's own quick start runs the container with seccomp unconfined, and our analysis tells you to check that the key actually gates the endpoints you expose and that the port stays private behind a reverse proxy.
Licences are simple here; the versions and the hardware assumptions are not
All five are Apache-2.0, which is worth saying plainly because it makes the licence conversation short. None of them asks you to publish changes if you run a modified copy inside your own network, and none attaches conditions to the code your agent runs. For a company standardising on one of them, this is not the decision that takes a week.
The decisions that take a week are versions and hardware. opensandbox-group/OpenSandbox ships its Python SDK on a 0.1 development line while the server sits on 1.1, and our analysis of OpenSandbox tells you to pin the SDK deliberately and to budget for cold starts. superradcompany/microsandbox is beta software that moves weekly, and our analysis tells you to pin the CLI to a specific release. anthropics/sandbox-runtime is a beta research preview whose configuration formats may still change. kubernetes-sigs/agent-sandbox expects you to pin a release tag, confirm that the manifest for that tag exists and look for a previous install before applying a new one. agent-infra/sandbox expects you to pin a release tag and confirm it exists in the registry you pull from.
One practical point closes this. The licence covers the tool. The code your agent writes, the data it reads and the secrets it holds stay under your own terms, and what you accept are the terms of the tool that runs it.
Bottom line
Take superradcompany/microsandbox when you want a single local microVM with no server to operate, anthropics/sandbox-runtime when you want operating system restrictions around a process you already run, agent-infra/sandbox when you want one container with a browser, a shell and a code server inside it, opensandbox-group/OpenSandbox when you want a control plane spanning Docker and Kubernetes, and kubernetes-sigs/agent-sandbox when you already run Kubernetes and need a stateful pod per agent. Before committing, confirm the host gives you KVM, WHP or Apple Silicon as the case requires, pin the version of every component you depend on, and check that your allowlist blocks what you think it blocks.
Sources
- E2B official site
- opensandbox-group/OpenSandbox repository
- opensandbox-group/OpenSandbox README
- superradcompany/microsandbox repository
- superradcompany/microsandbox README
- anthropics/sandbox-runtime repository
- anthropics/sandbox-runtime README
- kubernetes-sigs/agent-sandbox repository
- kubernetes-sigs/agent-sandbox README
- agent-infra/sandbox repository
- agent-infra/sandbox README