# ScratchRun

**Category:** 💻 Developer Tools  
**Repository:** https://github.com/ar-blues/scratchrun-mcp  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/scratchrun

## Description
Ephemeral MicroVM-isolated code execution for AI agents. Fresh VM per call, hard-purged after.

## Claude Desktop Quick Installation
Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low):

```json
"mcpServers": {
  "scratchrun": {
    "command": "npx",
    "args": ["-y","scratchrun"]
  }
}
```

## Documentation & README

# @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