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LLM Sandbox

Answer in brief

Python library that runs model-generated code through one API on Docker, Podman or Kubernetes, with Bubblewrap/nsjail local backends and an MCP server. A convenient backend-agnostic wrapper for teams that already run containers and want a Python-first code-execution layer.

By the Agent Sandboxes editors · Updated

Overview

LLM Sandbox "runs Large Language Model (LLM) generated code through a common API" over several backends: Docker, Podman and Kubernetes containers, and on Linux the Bubblewrap and NsJail OS sandboxes (which the README is explicit share the host kernel). It supports Python, JavaScript/Node.js, Java, C++, Go and R, extracts plots as artifacts, pools containers, keeps interactive Python sessions, and ships an MCP server so clients such as Claude Desktop can execute code in it. Examples cover eleven agent frameworks including LangChain and LlamaIndex.

It is a library rather than a service, so limits, lifetime and persistence are whatever the backend gives you. Security policies are advisory: is_safe() reports a verdict but does not stop run(). The Windows adapters are labelled "experimental adapters with different prerequisites and API limits". MIT-licensed; pip install llm-sandbox with extras per backend.

Notable

  • Backends: Docker, Podman, Kubernetes, Bubblewrap and NsJail (Linux), plus experimental Windows MXC and WSL2 adapters
  • Six languages (Python, JavaScript, Java, C++, Go, R) and an MCP server
  • README: "Security policies are advisory"

LLM Sandbox specifications

AttributeDetails
IsolationContainer per session on Docker, Podman or Kubernetes; optional Bubblewrap or NsJail backends on Linux that share the host kernel and are "not a VM boundary"; experimental Windows adapters (Windows MXC, WSL2 Bubblewrap)
DeploymentOpen-source project · Self-hostable
Open sourceYes (MIT)
SDKs and interfacesPython, MCP server
Cold start (vendor claim)Not documented
Max session lengthNot documented
PersistenceInteractive Python sessions keep state between runs; container pooling for reuse; file copy to and from the sandbox; artifact extraction of plots. Local Linux backends do not support images, pooling or interactive sessions
GPUNot documented
NetworkingNetwork isolation and resource limits (CPU, memory, time) per session; security policies are advisory (is_safe() returns a verdict without blocking run())
PricingFree (MIT)
Free tierFree to self-host
ComplianceNot documented
RegionsNot documented

Facts from LLM Sandbox’s public documentation, verified November 9, 2026. Performance numbers are vendor claims.

Strengths and trade-offs

Strengths

  • You want one Python API over Docker, Podman and Kubernetes
  • You need plots and files extracted from the sandbox for data-analysis agents
  • You run a desktop MCP client and want it to execute code in a container

Trade-offs

  • Isolation is only as strong as the container runtime; local Linux backends share the host kernel
  • Security policies do not block execution on their own
  • No documented startup figures, GPU support or hosted option

Good fit for: Python applications that need to run model-generated code in whatever container runtime they already have.

How LLM Sandbox compares

SandboxIsolationOpen sourceSelf-host / BYOCCold start (vendor)Max sessionSnapshots / pauseGPUSDKs
LLM SandboxDocker/Podman/K8s containerYesYes / NoNot documentedNot documentedNo / Not documentedNot documentedPython, MCP server
SWE-ReXDocker / Modal / FargateYesYes / NoNot documentedNot documentedNo / Not documentedNot documentedPython, REST API
OpenHands RuntimeDocker containerYesYes / NoNot documentedNot documentedNot documented / Not documentedNot documentedPython, JavaScript/TypeScript, REST API
Docker SandboxesMicroVMNoYes / NoNot documentedUntil removed (local)Yes / YesYessbx CLI, TypeScript (cloud), REST API (cloud)
Judge0isolate (namespaces/cgroups)YesYes / NoNot documented5 s wall (max 20 s)No / NoNoREST API, Python, JavaScript/TypeScript
bubblewrapLinux namespacesYesYes / NoNot documentedNot documentedNo / NoNot documentedCLI

See all LLM Sandbox alternatives →

Frequently asked questions

What is LLM Sandbox?
Python library that runs model-generated code through one API on Docker, Podman or Kubernetes, with Bubblewrap/nsjail local backends and an MCP server. A convenient backend-agnostic wrapper for teams that already run containers and want a Python-first code-execution layer.
How does LLM Sandbox isolate code?
LLM Sandbox documents its isolation as: Container per session on Docker, Podman or Kubernetes; optional Bubblewrap or NsJail backends on Linux that share the host kernel and are "not a VM boundary"; experimental Windows adapters (Windows MXC, WSL2 Bubblewrap).
Is LLM Sandbox open source?
Yes (MIT). It can be self-hosted.
How much does LLM Sandbox cost?
Free (MIT) Check the official pricing page for current rates.
What are the alternatives to LLM Sandbox?
Common alternatives include SWE-ReX, OpenHands Runtime, Docker Sandboxes, Judge0, bubblewrap. See LLM Sandbox alternatives for a full comparison.

Sources

  1. github.com/vndee/llm-sandbox

Cite this page

Agent Sandboxes. (2026). LLM Sandbox. agentsandboxes.org. Last reviewed November 9, 2026. https://agentsandboxes.org/sandboxes/llm-sandbox/

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