# MCP Security Sandboxing

> Implementing safe tool execution, resource isolation, and access control in MCP servers.

- Skill: `jcorpac/mcp-security-sandboxing` (Agent Skill)
- Install (CLI): `npx skillmds@latest add jcorpac/mcp-security-sandboxing`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jcorpac/mcp-security-sandboxing/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: jcorpac (https://skillmd.com/u/jcorpac)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/jcorpac/mcp-security-sandboxing

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# MCP Security & Sandboxing

Allowing an AI to run code or access data is powerful but risky.

## Key Strategies
- **Least Privilege**: Only grant the server access to the data it explicitly needs.
- **Input Sanitization**: Treat all model outputs as untrusted user input.
- **Memory Isolation**: Run tools in ephemeral containers (Docker) or sandboxed environments (Pyodide).

## Safety Guards
- **Human-in-the-loop**: Require manual approval for destructive actions.
- **Rate Limiting**: Prevent abuse or expensive runaway processes.
- **Auditing**: Log every tool call and its output for review.

## Best Practices
- **Secrets**: Never hardcode API keys; use environment variables or secret managers.
- **Timeout**: Set strict limits on tool execution time.