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MCP server for ScratchRun — ephemeral MicroVM code execution for AI agents

MCP ServersOfficial Registry0 stars0 forksJavaScriptUpdated today
Install in Claude Code / Claude Desktop
Method: Manual
Claude Code CLI
git clone https://github.com/ar-blues/scratchrun-mcp
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "scratchrun-mcp": {
      "command": "node",
      "args": ["/path/to/scratchrun-mcp/dist/index.js"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Clone https://github.com/ar-blues/scratchrun-mcp and follow its README for install instructions.
Use cases

MCP Servers overview

# @scratchrun/mcp-server

MCP server for [ScratchRun](https://scratchrun.dev) — ephemeral, MicroVM-isolated code execution for AI agents.

Each call runs in a fresh hardware-isolated MicroVM. The VM is hard-purged after execution. No state, no files, nothing persists between calls.

## Install

Add to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "scratchrun": {
      "command": "npx",
      "args": ["-y", "@scratchrun/mcp-server"],
      "env": {
        "SCRATCHRUN_API_KEY": "sr_live_your_key_here"
      }
    }
  }
}
```

Get an API key at [scratchrun.dev](https://scratchrun.dev).

## Tool: `scratchrun_exec`

Executes code in an ephemeral sandbox and returns stdout, stderr, exit code, and any output files.

**Parameters:**

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `runtime` | `python3.12` \| `python3.11` \| `node20` \| `bash` | yes | Runtime to use |
| `code` | string | yes | Code to execute |
| `timeout_ms` | integer | no | Timeout in ms (default 10000, max 30000) |
| `memory_mb` | integer | no | Memory limit in MB (default 256, max 512) |
| `env` | object | no | Environment variables — use for secrets, not code strings |
| `files` | object | no | Files to write before execution (path → content) |
| `return_files` | string[] | no | File paths to capture after execution (returned as base64) |

**Example — run Python and return a chart:**

```json
{
  "runtime": "python3.12",
  "code": "import matplotlib.pyplot as plt\nimport numpy as np\nx = np.linspace(0, 10, 100)\nplt.plot(x, np.sin(x))\nplt.savefig('/tmp/plot.png')",
  "return_files": ["/tmp/plot.png"]
}
```

Output files are returned as base64. Image files (PNG, JPG, SVG) are returned as MCP image content blocks and render inline in Claude.

## Isolation

- Hardware-virtualized MicroVM per execution (own kernel, not a shared-kernel container)
- `TerminateMicroVM` called unconditionally after every run — VM destroyed, never reused
- RFC 1918 + cloud metadata (`169.254.x.x`) always blocked at the network layer
- Read-only system filesystem via OverlayFS; `/tmp` is RAM-backed and gone with the VM

## Latency

~400ms median (warm pool). 2–8s cold start if the pool is empty.

## License

MIT

What people ask about scratchrun-mcp

What is ar-blues/scratchrun-mcp?

+

ar-blues/scratchrun-mcp is mcp servers for the Claude AI ecosystem. MCP server for ScratchRun — ephemeral MicroVM code execution for AI agents It has 0 GitHub stars and was last updated today.

How do I install scratchrun-mcp?

+

You can install scratchrun-mcp by cloning the repository (https://github.com/ar-blues/scratchrun-mcp) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is ar-blues/scratchrun-mcp safe to use?

+

ar-blues/scratchrun-mcp has not been audited yet by our security agent. Review the original repository on GitHub before using it in production.

Who maintains ar-blues/scratchrun-mcp?

+

ar-blues/scratchrun-mcp is maintained by ar-blues. The last recorded GitHub activity is from today, with 0 open issues.

Are there alternatives to scratchrun-mcp?

+

Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

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