developer-tools

Node.js Code Sandbox

ssdeanx

by ssdeanx

Node.js Code Sandbox offers a secure, isolated Docker environment to run Node.js code, npm dependencies, and shell comma

Provides a secure Docker-based environment for executing Node.js code with npm dependencies, shell commands, and file operations while maintaining proper isolation for testing and web development prototyping.

github stars

3

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Docker-based isolationDetached mode for serversResource limits built-in

best for

  • / Testing JavaScript libraries without local installation
  • / Web development prototyping and experiments
  • / Running untrusted code safely
  • / Automating browser tasks with Playwright

capabilities

  • / Execute JavaScript code in Docker containers
  • / Install npm dependencies on-demand
  • / Run shell commands inside sandboxes
  • / Create and manage files within containers
  • / Keep containers alive for long-running processes
  • / Control CPU and memory limits

what it does

Executes JavaScript code in isolated Docker containers with automatic npm dependency installation and file operations. Provides a secure sandbox environment for running Node.js scripts without affecting your local system.

about

Node.js Code Sandbox is a community-built MCP server published by ssdeanx that provides AI assistants with tools and capabilities via the Model Context Protocol. Node.js Code Sandbox offers a secure, isolated Docker environment to run Node.js code, npm dependencies, and shell comma It is categorized under developer tools.

how to install

You can install Node.js Code Sandbox in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Node.js Code Sandbox is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

🐢🚀 Node.js Sandbox MCP Server

Node.js server implementing the Model Context Protocol (MCP) for running arbitrary JavaScript in ephemeral Docker containers with on‑the‑fly npm dependency installation.

Website Preview

👉 Look at the official website

Features

  • Start and manage isolated Node.js sandbox containers
  • Execute arbitrary shell commands inside containers
  • Install specified npm dependencies per job
  • Run ES module JavaScript snippets and capture stdout
  • Tear down containers cleanly
  • Detached Mode: Keep the container alive after script execution (e.g. for long-running servers)

Note: Containers run with controlled CPU/memory limits.

Explore Cool Use Cases

If you want ideas for cool and powerful ways to use this library, check out the use cases section on the website It contains a curated list of prompts, examples, and creative experiments you can try with the Node.js Sandbox MCP Server.

⚠️ Prerequisites

To use this MCP server, Docker must be installed and running on your machine.

Tip: Pre-pull any Docker images you'll need to avoid delays during first execution.

Example recommended images:

  • node:lts-slim
  • mcr.microsoft.com/playwright:v1.52.0-noble
  • alfonsograziano/node-chartjs-canvas:latest

Getting started

In order to get started with this MCP server, first of all you need to connect it to a client (for example Claude Desktop).

Once it's running, you can test that it's fully working with a couple of test prompts:

  • Validate that the tool can run:

    Create and run a JS script with a console.log("Hello World")
    

    This should run a console.log and in the tool response you should be able to see Hello World.

  • Validate that you can install dependencies and save files

    Create and run a JS script that generates a QR code for the URL `https://nodejs.org/en`, and save it as `qrcode.png` **Tip:** Use the `qrcode` package.
    

    This should create a file in your mounted directory (for example the Desktop) called "qrcode.png"

Usage with Claude Desktop

Add this to your claude_desktop_config.json: You can follow the Official Guide to install this MCP server

{
  "mcpServers": {
    "js-sandbox": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "/var/run/docker.sock:/var/run/docker.sock",
        "-v",
        "$HOME/Desktop/sandbox-output:/root",
        "-e",
        "FILES_DIR=$HOME/Desktop/sandbox-output",
        "-e",
        "SANDBOX_MEMORY_LIMIT=512m", // optional
        "-e",
        "SANDBOX_CPU_LIMIT=0.75", // optional
        "alfonsograziano/node-code-sandbox-mcp"
      ]
    }
  }
}

or with NPX:

{
  "mcpServers": {
    "node-code-sandbox-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "node-code-sandbox-mcp"],
      "env": {
        "FILES_DIR": "/Users/alfonsograziano/Desktop/node-sandbox",
        "SANDBOX_MEMORY_LIMIT": "512m", // optional
        "SANDBOX_CPU_LIMIT": "0.75" // optional
      }
    }
  }
}

Note: Ensure your working directory points to the built server, and Docker is installed/running.

Docker

Run the server in a container (mount Docker socket if needed), and pass through your desired host output directory as an env var:

# Build locally if necessary
# docker build -t alfonsograziano/node-code-sandbox-mcp .

docker run --rm -it \
  -v /var/run/docker.sock:/var/run/docker.sock \
  -v "$HOME/Desktop/sandbox-output":"/root" \
  -e FILES_DIR="$HOME/Desktop/sandbox-output" \
  -e SANDBOX_MEMORY_LIMIT="512m" \
  -e SANDBOX_CPU_LIMIT="0.5" \
  alfonsograziano/node-code-sandbox-mcp stdio

This bind-mounts your host folder into the container at the same absolute path and makes FILES_DIR available inside the MCP server.

Usage with VS Code

Quick install buttons (VS Code & Insiders):

Install js-sandbox-mcp (NPX) Install js-sandbox-mcp (Docker)

Manual configuration: Add to your VS Code settings.json or .vscode/mcp.json:

"mcp": {
    "servers": {
        "js-sandbox": {
            "command": "docker",
            "args": [
                "run",
                "-i",
                "--rm",
                "-v", "/var/run/docker.sock:/var/run/docker.sock",
                "-v", "$HOME/Desktop/sandbox-output:/root",
                "-e", "FILES_DIR=$HOME/Desktop/sandbox-output",
                "-e", "SANDBOX_MEMORY_LIMIT=512m",
                "-e", "SANDBOX_CPU_LIMIT=1",
                "alfonsograziano/node-code-sandbox-mcp"
              ]
        }
    }
}

API

Tools

run_js_ephemeral

Run a one-off JS script in a brand-new disposable container.

Inputs:

  • image (string, optional): Docker image to use (default: node:lts-slim).
  • code (string, required): JavaScript source to execute.
  • dependencies (array of { name, version }, optional): NPM packages and versions to install (default: []).

Behavior:

  1. Creates a fresh container.
  2. Writes your index.js and a minimal package.json.
  3. Installs the specified dependencies.
  4. Executes the script.
  5. Tears down (removes) the container.
  6. Returns the captured stdout.
  7. If your code saves any files in the current directory, these files will be returned automatically.
    • Images (e.g., PNG, JPEG) are returned as image content.
    • Other files (e.g., .txt, .json) are returned as resource content.
    • Note: the file saving feature is currently available only in the ephemeral tool.

Tip: To get files back, simply save them during your script execution.

Example Call:

{
  "name": "run_js_ephemeral",
  "arguments": {
    "image": "node:lts-slim",
    "code": "console.log('One-shot run!');",
    "dependencies": [{ "name": "lodash", "version": "^4.17.21" }],
  },
}

Example to save a file:

import fs from 'fs/promises';

await fs.writeFile('hello.txt', 'Hello world!');
console.log('Saved hello.txt');

This will return the console output and the hello.txt file.

sandbox_initialize

Start a fresh sandbox container.

  • Input:
    • image (string, optional, default: node:lts-slim): Docker image for the sandbox
    • port (number, optional): If set, maps this container port to the host
  • Output: Container ID string

sandbox_exec

Run shell commands inside the running sandbox.

  • Input:
    • container_id (string): ID from sandbox_initialize
    • commands (string[]): Array of shell commands to execute
  • Output: Combined stdout of each command

run_js

Install npm dependencies and execute JavaScript code.

  • Input:

    • container_id (string): ID from sandbox_initialize
    • code (string): JS source to run (ES modules supported)
    • dependencies (array of { name, version }, optional, default: []): npm package names → semver versions
    • listenOnPort (number, optional): If set, leaves the process running and exposes this port to the host (Detached Mode)
  • Behavior:

    1. Creates a temp workspace inside the container
    2. Writes index.js and a minimal package.json
    3. Runs npm install --omit=dev --ignore-scripts --no-audit --loglevel=error
    4. Executes node index.js and captures stdout, or leaves process running in background if listenOnPort is set
    5. Cleans up workspace unless running in detached mode
  • Output: Script stdout or background execution notice

sandbox_stop

Terminate and remove the sandbox container.

  • Input:
    • container_id (string): ID from sandbox_initialize
  • Output: Confirmation message

Usage Tips

  • Session-based tools (sandbox_initializerun_jssandbox_stop) are ideal when you want to:
    • Keep a long-lived sandbox container open.
    • Run multiple commands or scripts in the same environment.
    • Incrementally install and reuse dependencies.
  • One-shot execution with run_js_ephemeral is perfect for:
    • Quick experiments or simple scripts.
    • Cases where you don’t need to maintain state or cache dependencies.
    • Clean, atomic runs without worrying about manual teardown.
  • Detached mode is useful when you want to:
    • Spin up servers or long-lived services on-the-fly
    • Expose and test endpoints from running containers

Choose the workflow that best fits your use-case!

Build

Compile and bundle:

npm install
npm run build

License

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

FAQ

What is the Node.js Code Sandbox MCP server?
Node.js Code Sandbox is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Node.js Code Sandbox?
This profile displays 54 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

List & Promote Your MCP Server

Share your MCP server with the developer community

GET_STARTED →
MCP server reviews

Ratings

4.554 reviews
  • Pratham Ware· Dec 28, 2024

    Node.js Code Sandbox is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Yuki Yang· Dec 28, 2024

    Node.js Code Sandbox is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Meera Malhotra· Dec 28, 2024

    Node.js Code Sandbox reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Evelyn Mensah· Dec 20, 2024

    Node.js Code Sandbox has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Ren Rahman· Dec 16, 2024

    We wired Node.js Code Sandbox into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Advait Desai· Dec 12, 2024

    I recommend Node.js Code Sandbox for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Yash Thakker· Nov 19, 2024

    Useful MCP listing: Node.js Code Sandbox is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Amina Lopez· Nov 19, 2024

    Useful MCP listing: Node.js Code Sandbox is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Meera Johnson· Nov 19, 2024

    We wired Node.js Code Sandbox into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Ren Singh· Nov 7, 2024

    Node.js Code Sandbox reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

showing 1-10 of 54

1 / 6