Best sandbox for Mastra agents in 2026

Q: What matters in a sandbox for Mastra?

Per-user machines that cost nothing idle. A Mastra app usually serves many users. Sandbox.getOrCreate("user-42") gives each user one named sandbox that pauses itself after 60 seconds with nothing happening and wakes with its files, memory and processes when that user returns. Packages without a build step. The default image has Python 3.12, Node.js 24, pandas, NumPy and matplotlib, and pip install works when the agent needs more. Steps that can take a while. A command runs up to the timeout you give it, so a long data job is one tool call, not a polling loop. One tool set across frameworks. The tools are AI SDK tools, so the same sandbox code serves a Mastra agent, an AI SDK route and a workflow step.

Q: When might another sandbox fit better?

Mastra's workspace features. If you want Mastra's workspace layer itself, with its filesystem abstraction and mounts, use one of the workspace providers Mastra lists; Runtime plugs in as tools instead.

Mastra agents take AI SDK tools as they are, so the best sandbox plugs in as tools and costs almost nothing while idle.

With Runtime a Mastra agent gets a full Linux microVM from one line, tools: runtimeTools(sbx), and pays for CPU only while code runs. The four tools run commands and read, write and list files in a Firecracker microVM with its own kernel, where pandas, NumPy and matplotlib are already installed. Twenty thousand three-minute data questions a month, each busy for 30 CPU-seconds, cost $34.17 on Runtime, $165.60 on E2B and $165.60 on Daytona at their published rates, checked 23 September to 2 October 2026.

How does Mastra connect an agent to a sandbox?

Mastra has two routes. Its workspaces attach a sandbox provider to an agent with workspace: new Workspace({ sandbox }), and Mastra's sandbox docs list Daytona, E2B, Modal, Vercel and Docker among the providers. Separately, any AI SDK tool can go straight into an agent's tools, which is how Runtime plugs in: no workspace, no provider package, and the same tools work in a plain generateText call.

Route	Where commands run	What you add
`LocalSandbox`, no isolation	The app's own host	Nothing; Mastra calls it not secure
`LocalSandbox` with bwrap or seatbelt	The host, with writes limited	Bubblewrap or macOS Seatbelt
A workspace sandbox provider	That provider's machines	The provider's Mastra package
`runtimeTools(sbx)`	A Runtime microVM your code created	`withruntime`, one line in `tools`

What matters in a sandbox for Mastra?

Per-user machines that cost nothing idle. A Mastra app usually serves many users. Sandbox.getOrCreate("user-42") gives each user one named sandbox that pauses itself after 60 seconds with nothing happening and wakes with its files, memory and processes when that user returns.
Packages without a build step. The default image has Python 3.12, Node.js 24, pandas, NumPy and matplotlib, and pip install works when the agent needs more.
Steps that can take a while. A command runs up to the timeout you give it, so a long data job is one tool call, not a polling loop.
One tool set across frameworks. The tools are AI SDK tools, so the same sandbox code serves a Mastra agent, an AI SDK route and a workflow step.

What does a Mastra data agent cost per month?

Twenty thousand questions, each three minutes on a 2 vCPU, 4 GiB sandbox and busy for 30 CPU-seconds, at each provider's published rates:

Provider	Isolation	CPU billed on	A month of questions
Runtime	Firecracker microVM	Measured use	$34.17
Vercel Sandbox	Firecracker microVM	Measured use	$106.13
E2B	Firecracker microVM	Every vCPU held	$165.60
Daytona	Containers by default	Every vCPU held	$165.60
Modal	gVisor, a shared kernel	The CPU requested	$237.96

Runtime costs 68% less than Vercel Sandbox and 86% less than Modal for the same month.

A run on Runtime, recorded 1 October 2026

TypeScriptimport { Agent } from "@mastra/core/agent";import { Sandbox } from "withruntime";import { runtimeTools } from "withruntime/ai";await using sbx = await Sandbox.create();const analyst = new Agent({  id: "analyst",  name: "Analyst",  instructions: "Answer with numbers you computed in the sandbox.",  model: "anthropic/claude-sonnet-4-6",  tools: runtimeTools(sbx),});const answer = await analyst.generate("Total revenue by region in sales.csv?", { maxSteps: 6 });console.log(answer.text);

We ran this agent's generate() loop with @mastra/core 1.71.0 and the AI SDK's mock model in place of Claude, so the model's two tool calls were scripted and Mastra ran them against a live sandbox:

textruntime_write_file sales.csv   Wrote 62 bytes to /workspace/sales.csvruntime_exec python3 -c "...groupby('region').revenue.sum()..."  exitCode 0  region  east     1250  south     950  west     1500

pandas was there with nothing installed first. Per-user sandboxes and the rest of the API are in Mastra in a sandbox.

When might another sandbox fit better?

Mastra's workspace features. If you want Mastra's workspace layer itself, with its filesystem abstraction and mounts, use one of the workspace providers Mastra lists; Runtime plugs in as tools instead.

Sources

Checked 1 October 2026.

Mastra sandboxes: workspaces, the provider list and the LocalSandbox isolation levels
Each provider's published rates, checked 23 September to 2 October 2026, as the pricing guide lists them
The recorded run: Runtime's TypeScript SDK with @mastra/core 1.71.0 and ai 7.0.87's MockLanguageModelV4, against production on 1 October 2026