How to Use the E2B MCP in Mastra AI

Add code execution to Mastra AI workflows using isolated sandboxes that fire up in milliseconds.

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Connect E2B MCP to Mastra AI

Create your Vinkius account to connect E2B to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup E2B with Mastra AI

Ask AI about this MCP

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Perplexity

Agentic code execution

Give your Mastra AI agents the ability to write and run scripts safely. The `create_sandbox` tool provides a fresh environment for every task. It handles complex logic that LLMs struggle with alone. You define the agent behavior and let the sandbox handle the heavy computation.

Reliable workflow cleanup

Use `kill_sandbox` within your Mastra AI workflow nodes to ensure environments don't persist longer than needed. It's a simple way to manage your infrastructure costs. If a workflow fails, you can trigger the termination tool to prevent zombie processes. This keeps your execution environment predictable.

Active environment monitoring

Keep tabs on your fleet of sandboxes using `list_sandboxes`. It returns metadata on every active instance your agents have spawned. This visibility helps you audit your agent activity. You see exactly what is running across your Mastra AI pipelines at any moment.

Setup guide

Set up E2B MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All E2B tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "e2b-mcp-client",
  servers: {
    "e2b-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "E2B Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to E2B tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent E2B transactions"
);
console.log(result.text);

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Why Choose Vinkius

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Real-time monitoring

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

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place for every integration

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Common questions about E2B MCP in Mastra AI

You instantiate the MCP client in your Mastra AI project and add the tools to your agent configuration. This gives the agent direct access to the sandbox lifecycle tools.

Yes, you can define retry logic in your Mastra AI workflow that spawns a new sandbox if the first attempt fails. This ensures your agentic loops remain resilient.

Since E2B runs as an MCP server, it works anywhere your Mastra AI code runs. Just make sure the server has access to your E2B API key.

Every sandbox uses Firecracker virtualization to isolate the code. This prevents the agent from touching the host machine or your Mastra AI core logic.

The sandbox only sees the files you explicitly copy into it. It has no access to your Mastra AI database or sensitive environment secrets unless you provide them.

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