Snipara Sandbox Integration

Snipara Sandbox is a Python execution layer that integrates with Snipara for context-aware code generation, explicitly started agents, and multi-step task execution across sandbox, docker, and trusted local backends. Sandbox jobs start only from an explicit user or workflow command; Snipara does not silently launch execution.

Installation

Or install manually:

pip install snipara-sandbox[all]

The current PyPI package is snipara-sandbox. Legacy command aliases remain available for existing installations.

Or install specific features:

Quick Start

snipara-sandbox init

snipara-sandbox run "Summarize the authentication flow"

snipara-sandbox run --env docker "Parse and analyze logs"

snipara-sandbox agent "Analyze all CSV files and generate a report"

Claude Code / Claude Desktop Setup

Add Snipara Sandbox as an MCP server to get Python execution in Claude. No API keys required for Snipara Sandbox itself.

Step 1: Install with MCP support

pip install snipara-sandbox[mcp]

Step 2: Add to your MCP configuration

Add to ~/.mcp.json (Claude Code) or ~/.claude/claude_desktop_config.json (Claude Desktop):

{

  "mcpServers": {

    "snipara-sandbox": {

      "command": "snipara-sandbox",

      "args": ["mcp-serve"]

    }

  }

}

Step 3: Add Snipara for context (optional but recommended)

Combine Snipara Sandbox with Snipara for context-aware code execution:

{

  "mcpServers": {

    "snipara-sandbox": {

      "command": "snipara-sandbox",

      "args": ["mcp-serve"]

    },

    "snipara": {

      "type": "http",

      "url": "https://api.snipara.com/mcp/YOUR_PROJECT",

      "headers": {

        "X-API-Key": "snp-YOUR-API-KEY"

      }

    }

  }

}

Available MCP Tools

Execution Environments

The standalone Python package can expose other runtime backends such as WebAssembly. The MCP execute_python tool itself selects sandbox, docker, or trusted local execution.

When to Use Snipara Sandbox vs Direct MCP

Use Direct Snipara MCP Tools For:

• Documentation Q&A- "What's the tech stack?"
• Code lookup- "Where is auth handled?"
• Simple retrieval- "List all API endpoints"

Use Snipara Sandbox For:

• Multi-step code tasks- "Implement OAuth integration"
• Complex reasoning- "Refactor auth to use JWT"
• Iterative refinement- "Optimize this function"
• Multi-file changes- "Add validation to all endpoints"

Python API

import asyncio

from snipara_sandbox import SniparaSandbox

async def main():

    sandbox = SniparaSandbox(

        model="openai/YOUR_MODEL",

        environment="docker",

        max_depth=4,

    )

    result = await sandbox.completion("Analyze and fix the auth bug")

    print(result.response)

asyncio.run(main())

Configuration

Create snipara-sandbox.toml in your project:

[snipara_sandbox]

backend = "litellm"

model = "openai/YOUR_MODEL"

environment = "docker"

max_depth = 4

# Snipara integration

snipara_api_key = "snp-..."

snipara_project_slug = "your-project"

# Docker settings

docker_image = "python:3.11-slim"

docker_memory = "512m"

Or use environment variables:

export SNIPARA_SANDBOX_MODEL=openai/YOUR_MODEL

export SNIPARA_SANDBOX_ENVIRONMENT=docker

export SNIPARA_API_KEY=snp-...

export SNIPARA_PROJECT_SLUG=my-project

CLI Commands

Safety Limits

Links

Next Steps