Python MCP Sandbox is an interactive Python code execution tool that allows users and LLMs to safely execute Python code and install packages in
MCP Sandbox becomes available to MCP clients through the mcp sandbox mcp server. Python MCP Sandbox is an interactive Python code execution tool that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.
Python MCP Sandbox is an interactive Python code execution tool that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.
Setup follows the standard MCP pattern: clone or install the server, then register it in your client's configuration file and restart the client. The configuration snippets on this page cover Claude Desktop, Claude Code and Cursor.
Before the server will start you need to supply one environment variable: YOUR_API_KEY. Keep credentials in your client's env block or a secrets manager rather than committing them.
Cloud and DevOps servers put infrastructure on speaking terms with your assistant, so "why is this broken?" is answered from real state rather than a generic checklist. MCP Sandbox sits in that group. Worth comparing against the other cloud devops servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.
## MCP Example Config for Online Demo
```json
{
"mcpServers": {
"mcpSandbox": {
"command": "npx",
"args": ["-y", "supergateway", "--sse", "http://115.190.87.78/sse?api_key=<API_KEY>"]
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| YOUR_API_KEY | Credential the server authenticates with. | Yes |
Manage your whole Supabase project in conversation — database, auth, storage, Edge Functions and branches.
Stop letting your assistant hallucinate n8n node parameters — this server hands it the real schemas, templates and validation.
AWS Labs' official server suite — current AWS docs, CDK guidance, cost analysis and service tools.
Cloud browsers for AI agents — automation sessions that run in Browserbase's fleet, not on your machine.
Workers, KV, R2 and D1 by conversation — Cloudflare's official remote servers for building and observability.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.