# ai.smithery/STUzhy-py_execute_mcp

> Use this tool when you need to execute Python code securely without local setup, to solve problems such as testing, validating, or running untrusted code. It takes Python code and inline dependencies as input and outputs the execution results, providing a secure sandbox environment. Ideal for use cases where local setup is not feasible or code security is a concern.

Canonical page: https://skillsregistry.net/skills/ai-smithery-stuzhy-py-execute-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ai-smithery-stuzhy-py-execute-mcp

## Description

Run Python code in a secure sandbox without local setup. Declare inline dependencies and execute s…

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.smithery%2FSTUzhy-py_execute_mcp)

## Use it

MCP endpoint published by the skill: `https://server.smithery.ai/@STUzhy/py_execute_mcp/mcp`

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ai-smithery-stuzhy-py-execute-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-smithery-stuzhy-py-execute-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-smithery-stuzhy-py-execute-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt