Vinkius
E2B

E2B MCP for AI. Run agent code in secure, isolated sandboxes.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

E2B MCP on Cursor AI Code EditorE2B MCP on Claude Desktop AppE2B MCP on OpenAI Agents SDKE2B MCP on Visual Studio CodeE2B MCP on GitHub Copilot AI AgentE2B MCP on Google Gemini AIE2B MCP on Lovable AI DevelopmentE2B MCP on Mistral AI AgentsE2B MCP on Amazon AWS Bedrock

Connect to your AI in seconds.

E2B provides secure cloud sandboxes for running code, letting your agent execute Python, JavaScript, or shell commands in isolated Firecracker microVMs.

Spin up environments in milliseconds—it's perfect for safely testing untrusted logic without risking core infrastructure.

What your AI can do

Create sandbox

Starts an isolated Linux virtual machine environment using templates like 'python3', 'node', or 'base'.

Kill sandbox

Stops and permanently deletes a running sandbox, freeing up the allocated computing resources.

List sandboxes

Shows a list of all currently active sandboxes in your account, detailing their status and resource usage.

Launch isolated code runtimes

Starts a new micro-isolated Linux environment for running specific languages like Python or Node.js.

Monitor active environments

Retrieves a list of every sandbox currently running, showing its status and resource usage.

Cleanly terminate resources

Permanently deletes a specific sandbox environment to release associated compute cycles and storage space.

Included with Plan

Waiting for input…

AI Agent

E2B: 3 Tools for Sandbox Management

Manage the full lifecycle of secure execution environments, from initial setup using create_sandbox to monitoring with list_sandboxes and cleanup with kill_sandbox.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using E2B on Vinkius

Create Sandbox

Starts an isolated Linux virtual machine environment using templates like 'python3', 'node', or 'base'.

Kill Sandbox

Stops and permanently deletes a running sandbox, freeing up the allocated computing...

List Sandboxes

Shows a list of all currently active sandboxes in your account, detailing their...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The E2B integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on every call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with E2B, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,100+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Every connection is secured and compliant automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog every week
E2B MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by E2B. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

VINKIUS INFRASTRUCTURE

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

The old way: manual setup and high risk.

Today, if your agent needs to run Python code or test a script, someone has to manually set up a virtual machine (VM) on a dedicated server. This involves logging into the command line, installing dependencies like pandas, and then running the script. It's slow, error-prone, and you always worry about forgetting to shut down that VM, which leads directly to wasted compute cycles and cost overruns.

With this MCP, your agent handles it all automatically. You just tell it what code to run, specify the template, and it spins up an isolated environment instantly. The output is clean, contained, and ready for the next step in the workflow.

Manage your entire sandbox lifecycle with `kill_sandbox`.

The biggest headache used to be resource cleanup. You'd run a script using `create_sandbox`, and even after the code finished, you were left with an active, running VM hanging around that cost money and cluttered your monitoring dashboard. Finding these 'ghost' sandboxes was tedious.

Now, when you are done, just use `kill_sandbox`. That single call guarantees termination—it shuts down the compute cycle *and* deletes the filesystem contents. It’s clean, reliable resource management.

What your AI can actually do with this

When you build AI agents that need to run actual code—say, processing a file or making an API call with Python—you can't just let them run it directly on your main server. The risk is too high. This MCP lets your agent spin up completely isolated environments where all the action happens.

It’s like giving your AI client its own tiny, secure computer that only exists for the task at hand. Your agent can launch a sandbox with a specific setup, run the script, and then shut it down clean. You get full visibility into what's running using one set of tools, and you can terminate anything when you’re done.

Because this whole system is hosted on Vinkius, your agent connects once to manage these environments across any compatible AI client.

Built · Hosted · Managed by Vinkius E2B MCP - Secure Code Sandbox Execution
Server ID 019d758b-1ee8-73d2-bcb9-fc66121d9410
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

How fast is it to create a sandbox using create_sandbox? +

Sandboxes start up quickly; they launch in about 150 milliseconds. This speed makes them ideal for real-time agent interactions where latency matters.

Do I have to use kill_sandbox after I run a script? +

Yes, you should always call kill_sandbox when the work is done. It releases the allocated resources and prevents accidental billing or resource exhaustion from abandoned environments.

What templates are available for create_sandbox? +

The service supports several predefined templates, including 'base' (the default), 'python3', and 'node'. You pick the template that matches the language you need to run code in.

Can I check if my sandboxes are running with list_sandboxes? +

Absolutely. list_sandboxes lets you see all active environments, giving you a clear overview of resource usage and status across your account.

How does using `create_sandbox` ensure that code running in one sandbox cannot affect others? +

It uses Firecracker microVMs for strong isolation. This architecture gives every sandbox its own kernel and filesystem, guaranteeing that even if a script crashes or runs malicious code, it stays contained within that specific environment.

If I forget to call `kill_sandbox`, will it impact my billing? +

While resources are designed to be managed, leaving sandboxes running increases resource consumption and associated costs. Always calling kill_sandbox immediately after your task finishes is the best way to stop accruing charges.

Can I set a custom execution time limit when using the `create_sandbox` tool? +

Yes, you can adjust the timeout parameter. Although the default is 300 seconds, specifying a shorter or longer timeout ensures the sandbox matches your script's expected runtime and prevents unnecessary resource retention.

What detailed metrics does `list_sandboxes` provide besides status? +

It gives you more than just active status. You can see the template used for each environment, along with details on its current resource usage and when it was last started, which is critical for monitoring.

How secure are E2B sandboxes? +

E2B sandboxes run as dedicated Firecracker microVMs — the same technology used by AWS Lambda and Fargate. Each sandbox has its own Linux kernel, filesystem, and network stack, providing hardware-level isolation. Code running in a sandbox cannot access your host system, other sandboxes, or any external resources unless explicitly configured.

What programming languages are supported? +

E2B supports Python, JavaScript/TypeScript, R, Java, and Bash out of the box. You can also create custom sandbox templates with any pre-installed tools, libraries, or system dependencies. The base template provides a full Ubuntu Linux environment where you can install anything via apt or pip.

How does E2B pricing work? +

E2B uses usage-based pricing billed per second of compute time. The free Hobby plan includes a one-time $100 credit (no credit card required), up to 20 concurrent sandboxes, and 1-hour maximum session length. The Pro plan starts at $150/month with 24-hour sessions and higher concurrency limits.

Built & Managed by Vinkius 30s setup 3 tools

We've already built the connector for E2B. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 3 tools are live and waiting. You're up and running in seconds.

Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on Windsurf Windsurf
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
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