302AI Sandbox MCP Server▌
by 302ai
302AI Sandbox MCP Server: an MCP (Model Context Protocol) server for Claude Desktop connecting to 302AI APIs for seamles
A Model Context Protocol (MCP) server for Claude Desktop that connects to 302AI's API services, allowing users to integrate and leverage 302AI capabilities through a structured communication interface.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / AI assistants needing safe code execution
- / Testing code snippets without local setup
- / Educational environments requiring isolated execution
- / Development workflows with temporary containers
capabilities
- / Execute code in secure sandboxes
- / Create and manage multiple sandbox instances
- / Run command line operations in containers
- / Import and export files to/from sandboxes
- / Query file information within sandbox environments
- / Destroy sandbox instances when finished
what it does
Provides a code sandbox environment through 302AI's API services, allowing AI assistants to safely execute code in isolated containers.
about
302AI Sandbox MCP Server is a community-built MCP server published by 302ai that provides AI assistants with tools and capabilities via the Model Context Protocol. 302AI Sandbox MCP Server: an MCP (Model Context Protocol) server for Claude Desktop connecting to 302AI APIs for seamles It is categorized under developer tools.
how to install
You can install 302AI Sandbox MCP Server 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
302AI Sandbox MCP Server is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
<p align="center">🤖 302AI Sandbox MCP Server🚀✨</p>
<p align="center">An MCP service with code sandbox that allows AI assistants to safely execute arbitrary code.</p> <p align="center"><a href="https://www.npmjs.com/package/@302ai/sandbox-mcp" target="blank"><img src="https://file.302.ai/gpt/imgs/github/20250102/72a57c4263944b73bf521830878ae39a.png" /></a></p > <p align="center"><a href="README_zh.md">中文</a> | <a href="README.md">English</a> | <a href="README_ja.md">日本語</a></p>
Previews
Here are some usage examples


Here is the list of supported tools

✨ Features ✨
- 🔧 Dynamic Loading - Automatically update tool list from remote server.
- 🌐 Multi modes supported, you can use
stdinmode locally, or host it as a remote HTTP server
🚀 Tool List
- One-click Code Execution
- Create Sandbox
- Query Your Sandbox List
- Destroy Sandbox
- Run-Code
- Run Command Line
- Query File Information at Specified Path
- Import File Data into Sandbox
- Export Sandbox Files
Development
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Installation
To use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"302ai-sandbox-mcp": {
"command": "npx",
"args": ["-y", "@302ai/sandbox-mcp"],
"env": {
"302AI_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
To use with Cherry Studio, add the server config:
{
"mcpServers": {
"Li2ZXXJkvhAALyKOFeO4N": {
"name": "302ai-sandbox-mcp",
"description": "",
"isActive": true,
"registryUrl": "",
"command": "npx",
"args": [
"-y",
"@302ai/[email protected]"
],
"env": {
"302AI_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
To use with ChatWise, copy the following content to clipboard
{
"mcpServers": {
"302ai-sandbox-mcp": {
"command": "npx",
"args": ["-y", "@302ai/sandbox-mcp"],
"env": {
"302AI_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
Go to Settings -> Tools -> Add button -> Select Import from Clipboard

Find Your 302AI_API_KEY here
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
✨ About 302.AI ✨
302.AI is an enterprise-oriented AI application platform that offers pay-as-you-go services, ready-to-use solutions, and an open-source ecosystem.✨
- 🧠 Integrates the latest and most comprehensive AI capabilities and brands, including but not limited to language models, image models, voice models, and video models.
- 🚀 Develops deep applications based on foundation models - we develop real AI products, not just simple chatbots
- 💰 Zero monthly fee, all features are pay-per-use, fully open, achieving truly low barriers with high potential.
- 🛠 Powerful management backend for teams and SMEs - one person manages, many people use.
- 🔗 All AI capabilities provide API access, all tools are open source and customizable (in progress).
- 💡 Strong development team, launching 2-3 new applications weekly, products updated daily. Developers interested in joining are welcome to contact us.
FAQ
- What is the 302AI Sandbox MCP Server MCP server?
- 302AI Sandbox MCP Server 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 302AI Sandbox MCP Server?
- This profile displays 61 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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.
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Ratings
4.7★★★★★61 reviews- ★★★★★William Patel· Dec 28, 2024
I recommend 302AI Sandbox MCP Server for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Sakura Ramirez· Dec 24, 2024
We wired 302AI Sandbox MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Aanya Martin· Dec 20, 2024
We evaluated 302AI Sandbox MCP Server against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★William Flores· Dec 20, 2024
302AI Sandbox MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Charlotte Torres· Dec 8, 2024
302AI Sandbox MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Hiroshi Abebe· Nov 19, 2024
302AI Sandbox MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ren Ndlovu· Nov 11, 2024
302AI Sandbox MCP Server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★William Haddad· Nov 11, 2024
According to our notes, 302AI Sandbox MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Harper Harris· Nov 3, 2024
302AI Sandbox MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Sakura Sanchez· Oct 22, 2024
We wired 302AI Sandbox MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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