---
name: e2b-sandbox
description: Execute AI-generated code in secure isolated E2B cloud sandboxes with advanced monitoring, MCP gateway integration (200+ tools), and multi-language support. Use for running Python/JavaScript/TypeScript/Bash code, managing sandbox lifecycle (create, pause, resume, kill, list, connect), monitoring metrics (CPU, memory, disk), handling lifecycle events, uploading/downloading files, streaming command output, environment variable management, and integrating LLMs with code execution capabilities.
---

# E2B Sandbox Skill

This skill provides comprehensive guidance for using E2B sandboxes - secure, isolated cloud VMs for executing AI-generated code with advanced monitoring, event handling, and integration capabilities.

## What is E2B?

E2B provides secure isolated sandboxes (small VMs) in the cloud that start very quickly (~150ms). Each sandbox has:
- Isolated filesystem (1GB Hobby tier, 5GB Pro tier)
- Full code execution capabilities (Python, JavaScript, TypeScript, Bash)
- Default lifetime of 5 minutes (configurable)
- Network access capabilities
- Real-time metrics monitoring (CPU, memory, disk)
- Lifecycle event tracking and webhooks
- MCP Gateway for 200+ tool integrations

## Core Concepts

### Sandbox Lifecycle

**Creating a Sandbox:**
```python
from e2b_code_interpreter import Sandbox

# Create with default 5 minute timeout
sandbox = Sandbox.create()

# Create with custom timeout (in seconds)
sandbox = Sandbox.create(timeout=60)

# With auto-pause (beta)
sandbox = Sandbox.beta_create(
    auto_pause=True,
    timeout=10 * 60  # 10 minutes
)

# With metadata for tracking
sandbox = Sandbox.create(
    metadata={'userId': '123', 'env': 'dev'}
)

# With environment variables
sandbox = Sandbox.create(
    envs={'API_KEY': 'secret_value'}
)
```

**JavaScript:**
```javascript
import { Sandbox } from '@e2b/code-interpreter'

// Create with metadata and env vars
const sandbox = await Sandbox.create({
  timeout: 60000,  // milliseconds
  metadata: { userId: '123' },
  envs: { API_KEY: 'secret_value' }
})
```

**Changing Timeout During Runtime:**
```python
# Reset timeout to 30 seconds from now
sandbox.set_timeout(30)
```

**Getting Sandbox Info:**
```python
info = sandbox.get_info()
# Returns: sandboxId, templateId, name, metadata, startedAt, endAt
```

**Shutting Down:**
```python
# Terminate sandbox immediately
sandbox.kill()

# Or kill by ID
Sandbox.kill(sandbox_id)
```

### Sandbox Management

**List Sandboxes:**
```python
# List with pagination
paginator = Sandbox.list()
sandboxes = paginator.next_items()

# Filter by state
paginator = Sandbox.list(query={'state': ['running', 'paused']})

# Filter by metadata
paginator = Sandbox.list(
    query={'metadata': {'userId': '123', 'env': 'dev'}}
)

# Advanced pagination
paginator = Sandbox.list(limit=100, next_token='<token>')
while paginator.has_next:
    items = paginator.next_items()
```

**Connect to Running Sandbox:**
```python
# Connect by ID
sandbox = Sandbox.connect(sandbox_id)

# Or reconnect to current
sandbox = sandbox.connect()
```

**JavaScript:**
```javascript
// List and filter
const paginator = Sandbox.list({
  query: {
    state: ['running'],
    metadata: { userId: '123' }
  }
})
const sandboxes = await paginator.nextItems()

// Connect to existing
const sandbox = await Sandbox.connect(sandboxId)
```

### Monitoring & Metrics

**Get Sandbox Metrics:**
```python
import time

# Wait for metrics to collect (every 5 seconds)
time.sleep(10)

metrics = sandbox.get_metrics()
# Returns: [{timestamp, cpuUsedPct, cpuCount, memUsed, memTotal, diskUsed, diskTotal}]

# Or by ID
metrics = Sandbox.get_metrics(sandbox_id)
```

**JavaScript:**
```javascript
await new Promise(resolve => setTimeout(resolve, 10000))

const metrics = await sandbox.getMetrics()
// Returns array of timestamped metrics
```

**CLI:**
```bash
e2b sandbox metrics <sandbox_id>
# Shows: CPU, Memory, Disk usage over time
```

**Lifecycle Events (REST API):**
```python
import requests

# Get events for specific sandbox
response = requests.get(
    f'https://api.e2b.app/events/sandboxes/{sandbox_id}',
    headers={'X-API-Key': E2B_API_KEY}
)
events = response.json()

# Get latest 10 events for all sandboxes
response = requests.get(
    'https://api.e2b.app/events/sandboxes?limit=10',
    headers={'X-API-Key': E2B_API_KEY}
)
```

Event types: `sandbox.lifecycle.created`, `sandbox.lifecycle.updated`, `sandbox.lifecycle.paused`, `sandbox.lifecycle.resumed`, `sandbox.lifecycle.killed`

See `docs/monitoring-and-events.md` for webhook configuration.

### Running Code

**Execute Python Code (Default):**
```python
# Run Python code and get results
execution = sandbox.run_code('print("hello world")')

# Access results
print(execution.text)        # Combined output text
print(execution.logs.stdout)  # Standard output
print(execution.logs.stderr)  # Standard error
print(execution.results)      # Execution results (charts, tables, etc.)
print(execution.error)        # Runtime errors if any
```

**Execute JavaScript/TypeScript:**
```python
# JavaScript
execution = sandbox.run_code(
    'console.log("Hello from JS")',
    language='javascript'  # or 'js'
)

# TypeScript with top-level await and ESM imports
execution = sandbox.run_code('''
import axios from "axios";
const response = await axios.get("https://api.github.com/status");
response.data;
''', language='typescript')  # or 'ts'
```

**Execute Bash:**
```python
execution = sandbox.run_code(
    'ls -la /home/user',
    language='bash'
)
```

**With Environment Variables:**
```python
# Scoped to this execution only
execution = sandbox.run_code(
    'import os; print(os.environ.get("MY_VAR"))',
    envs={'MY_VAR': 'my_value'}
)
```

**JavaScript:**
```javascript
// Python (default)
const exec = await sandbox.runCode('print("hello")')

// JavaScript/TypeScript
const exec = await sandbox.runCode('console.log("hello")', {
  language: 'js',
  envs: { MY_VAR: 'value' }
})
```

### Running Commands

**Execute Bash Commands:**
```python
# Run terminal commands
result = sandbox.commands.run('ls -l')
print(result)

# With environment variables
result = sandbox.commands.run(
    'echo $MY_VAR',
    envs={'MY_VAR': '123'}
)
```

**Streaming Output:**
```python
# Stream stdout/stderr in real-time
process = sandbox.commands.run(
    'for i in {1..5}; do echo "Line $i"; sleep 1; done',
    on_stdout=lambda data: print(f"OUT: {data}"),
    on_stderr=lambda data: print(f"ERR: {data}")
)
```

**Background Commands:**
```python
# Run in background, returns immediately
command = sandbox.commands.run(
    'echo hello; sleep 10; echo world',
    background=True,
    on_stdout=lambda data: print(data)
)

# Kill later
command.kill()
```

**JavaScript:**
```javascript
// Streaming
await sandbox.commands.run('echo hello', {
  onStdout: (data) => console.log(data),
  onStderr: (data) => console.error(data)
})

// Background
const cmd = await sandbox.commands.run('sleep 100', {
  background: true
})
await cmd.kill()
```

### Environment Variables

Three scoping levels:

1. **Global (sandbox-wide):**
```python
sandbox = Sandbox.create(envs={'API_KEY': 'value'})
```

2. **Code execution scope:**
```python
sandbox.run_code(code, envs={'MY_VAR': 'value'})
```

3. **Command execution scope:**
```python
sandbox.commands.run(cmd, envs={'MY_VAR': 'value'})
```

**Default Environment Variables:**
- `E2B_SANDBOX=true` - Indicates code is running in E2B
- `E2B_SANDBOX_ID` - Current sandbox ID
- `E2B_TEAM_ID` - Team ID that created sandbox
- `E2B_TEMPLATE_ID` - Template used for sandbox

### File Operations

**Upload Files:**
```python
import fs

# Read local file
content = fs.read_file('local/file.csv')

# Upload to sandbox (absolute path required)
file_info = sandbox.files.write('/home/user/data.csv', content)
print(file_info.path)  # Path in sandbox
```

**Download Files:**
```python
# Download file from sandbox
content = sandbox.files.read('/home/user/output.png')

# Save locally
fs.write_file('local/output.png', content)
```

**List Files:**
```python
# List files in directory
files = sandbox.files.list('/')
for file in files:
    print(file)
```

**Watch for Changes:**
```python
# Monitor filesystem changes
watcher = sandbox.files.watch('/home/user')
watcher.on_change(lambda event: print(f"Changed: {event}"))
```

See `docs/filesystem.md` for complete filesystem API.

### Sandbox Persistence (Beta)

**Pause and Resume:**
```python
# Pause sandbox (saves filesystem + memory state)
sandbox.beta_pause()
print(f"Paused sandbox: {sandbox.sandbox_id}")

# Resume later by reconnecting
resumed = sandbox.connect()

# Or connect by ID
resumed = Sandbox.connect(sandbox_id)
```

**List Paused Sandboxes:**
```python
# Get paginated list of paused sandboxes
paginator = Sandbox.list(query={'state': ['paused']})
sandboxes = paginator.next_items()
```

**Important Notes:**
- Pausing takes ~4 seconds per 1 GiB of RAM
- Resuming takes ~1 second
- Sandbox can be used for up to 30 days
- When sandbox resumes, timeout resets to default (5 minutes) or custom value

## Advanced Features

### MCP Gateway (200+ Tool Integrations)

E2B provides built-in access to 200+ MCP (Model Context Protocol) servers for integrating external tools.

**Enable MCP Servers:**
```python
# Python (JS SDK)
sandbox = Sandbox.create(
    mcp={
        'browserbase': {
            'apiKey': os.environ['BROWSERBASE_API_KEY'],
            'geminiApiKey': os.environ['GEMINI_API_KEY'],
            'projectId': os.environ['BROWSERBASE_PROJECT_ID']
        },
        'exa': {'apiKey': os.environ['EXA_API_KEY']},
        'notion': {'internalIntegrationToken': os.environ['NOTION_API_KEY']}
    }
)

# Get MCP URL and token
mcp_url = sandbox.get_mcp_url()
mcp_token = sandbox.get_mcp_token()
```

**Connect from Outside Sandbox:**
```javascript
import { Client } from '@modelcontextprotocol/sdk/client/index.js'
import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp.js'

const client = new Client({ name: 'e2b-mcp-client', version: '1.0.0' })

const transport = new StreamableHTTPClientTransport(
    new URL(sandbox.getMcpUrl()),
    {
        requestInit: {
            headers: { 'Authorization': `Bearer ${await sandbox.getMcpToken()}` }
        }
    }
)

await client.connect(transport)
const tools = await client.listTools()
```

**MCP Server Categories:**
- Data & Databases: MongoDB, PostgreSQL, Redis, Elasticsearch, Astra DB
- Cloud: AWS, Azure, Google Cloud, Kubernetes
- Web & Content: Firecrawl, Brave Search, Perplexity, DuckDuckGo, Tavily
- Business: Slack, Notion, GitHub, Jira, Confluence, HubSpot
- Development: GitHub Chat, JetBrains IDE, ast-grep, Semgrep
- AI: OpenAI, Browserbase, Hugging Face, ElevenLabs
- Finance: Stripe, Razorpay, Mercado Pago

See `docs/mcp-gateway.md` for complete list and configuration.

### Custom Templates

Build custom sandbox environments with specific dependencies:

```bash
# Using E2B CLI
e2b template build

# Specify CPU/RAM in e2b.toml
cpu_count = 2
memory_mb = 2048

# Add start commands
start_cmd = "python app.py"

# Add readiness checks
ready_cmd = "curl localhost:8000/health"
```

See `docs/custom-templates.md` for Build System 2.0 details.

### E2B CLI

```bash
# Authenticate
e2b auth login

# List sandboxes
e2b sandbox list

# Get metrics
e2b sandbox metrics <sandbox_id>

# Build custom template
e2b template build

# Connect to sandbox
e2b sandbox connect <sandbox_id>
```

## Integration Patterns

### Connecting LLMs to E2B

E2B works with any LLM via tool use (function calling). The general pattern:

1. Define a tool/function for code execution
2. LLM generates code
3. Execute code in E2B sandbox
4. Return results to LLM

**Example with Tool Use:**
```python
from anthropic import Anthropic
from e2b_code_interpreter import Sandbox

# Define tool
tools = [{
    "name": "execute_python",
    "description": "Execute python code in a Jupyter notebook cell and return result",
    "input_schema": {
        "type": "object",
        "properties": {
            "code": {
                "type": "string",
                "description": "The python code to execute in a single cell"
            }
        },
        "required": ["code"]
    }
}]

# Create Anthropic client
client = Anthropic()

# Send message with tools
message = client.messages.create(
    model="claude-3-5-sonnet-20240620",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": "Calculate how many r's are in the word 'strawberry'"
    }],
    tools=tools
)

# Execute tool if called
if message.stop_reason == "tool_use":
    tool_use = next(block for block in message.content if block.type == "tool_use")
    if tool_use.name == "execute_python":
        with Sandbox.create() as sandbox:
            code = tool_use.input['code']
            execution = sandbox.run_code(code)
            result = execution.text
            print(result)
```

### Data Analysis Pattern

For data analysis workflows:

1. Create sandbox
2. Upload dataset
3. LLM generates analysis code
4. Execute in sandbox
5. Extract results (charts, tables, data)

```python
# Upload dataset
content = fs.read_file('dataset.csv')
dataset_path = sandbox.files.write('/home/user/dataset.csv', content)

# Run analysis code (generated by LLM)
execution = sandbox.run_code(analysis_code)

# Extract chart if generated
for result in execution.results:
    if result.png:
        # PNG is base64 encoded
        fs.write_file('chart.png', result.png, encoding='base64')
```

### Multi-User Session Management

```python
# Create sandbox per user with metadata
sandbox = Sandbox.create(
    metadata={'userId': user_id, 'sessionId': session_id}
)

# Later: Find user's sandboxes
paginator = Sandbox.list(
    query={'metadata': {'userId': user_id}}
)
user_sandboxes = paginator.next_items()

# Reconnect to existing session
if user_sandboxes:
    sandbox = Sandbox.connect(user_sandboxes[0].sandbox_id)
```

## Best Practices

### Resource Management

1. **Always clean up sandboxes:**
```python
# Use context manager (recommended)
with Sandbox.create() as sandbox:
    # Your code here
    pass  # Sandbox automatically killed on exit

# Or manually
sandbox = Sandbox.create()
try:
    # Your code here
    pass
finally:
    sandbox.kill()
```

2. **Set appropriate timeouts:**
   - Short tasks: 60-120 seconds
   - Long-running analysis: 300-600 seconds
   - Use auto-pause for interactive sessions

3. **Use persistence wisely:**
   - Pause sandboxes between user interactions
   - Don't pause for short breaks (<5 minutes)
   - Kill sandboxes when truly done

4. **Monitor resource usage:**
```python
# Check metrics before intensive operations
metrics = sandbox.get_metrics()
if metrics:
    latest = metrics[-1]
    if latest['cpuUsedPct'] > 80:
        print("Warning: High CPU usage")
```

### Code Execution

1. **Handle errors gracefully:**
```python
execution = sandbox.run_code(code)

if execution.error:
    print(f"Error: {execution.error.name}")
    print(f"Message: {execution.error.value}")
    print(f"Traceback: {execution.error.traceback}")
else:
    print(execution.text)
```

2. **Process results by type:**
```python
for result in execution.results:
    if result.png:
        # Handle chart/image
        save_image(result.png)
    elif result.text:
        # Handle text output
        print(result.text)
```

3. **Use appropriate language:**
```python
# Python for data analysis
sandbox.run_code('import pandas as pd; df.describe()')

# JavaScript for async API calls
sandbox.run_code('await fetch(url)', language='js')

# Bash for system operations
sandbox.run_code('tar -xzf archive.tar.gz', language='bash')
```

### File Operations

1. **Always use absolute paths:**
```python
# Good
sandbox.files.write('/home/user/data.csv', content)

# Bad (relative paths may not work as expected)
sandbox.files.write('data.csv', content)
```

2. **Upload files before executing code:**
```python
# Upload dataset first
sandbox.files.write('/home/user/data.csv', dataset)

# Then run code that uses it
code = "import pandas as pd; df = pd.read_csv('/home/user/data.csv')"
sandbox.run_code(code)
```

### Sandbox Discovery

1. **Use metadata for tracking:**
```python
# Tag sandboxes with identifying information
sandbox = Sandbox.create(metadata={
    'userId': '123',
    'purpose': 'data-analysis',
    'created': datetime.now().isoformat()
})

# Find and reconnect
paginator = Sandbox.list(query={'metadata': {'userId': '123'}})
```

2. **Clean up orphaned sandboxes:**
```python
# Find all running sandboxes
paginator = Sandbox.list(query={'state': ['running']})
sandboxes = paginator.next_items()

# Kill old ones
for sbx in sandboxes:
    if should_cleanup(sbx):
        Sandbox.kill(sbx.sandbox_id)
```

## Common Patterns

### Pattern 1: One-shot Code Execution

```python
with Sandbox.create() as sandbox:
    result = sandbox.run_code(llm_generated_code)
    return result.text
```

### Pattern 2: Multi-step Analysis

```python
sandbox = Sandbox.create(timeout=300)
try:
    # Step 1: Upload data
    sandbox.files.write('/home/user/data.csv', data)

    # Step 2: Load and explore
    sandbox.run_code("import pandas as pd; df = pd.read_csv('/home/user/data.csv')")

    # Step 3: Analyze (code from LLM)
    result = sandbox.run_code(analysis_code)

    # Step 4: Extract results
    for r in result.results:
        if r.png:
            save_chart(r.png)
finally:
    sandbox.kill()
```

### Pattern 3: Interactive Session with Persistence

```python
# Initial creation
sandbox = Sandbox.beta_create(auto_pause=True, timeout=600)

# Do some work
sandbox.run_code(initial_code)

# Pause when user is inactive
sandbox.beta_pause()
save_sandbox_id(sandbox.sandbox_id)

# Later: Resume when user returns
sandbox = Sandbox.connect(saved_sandbox_id)
sandbox.run_code(next_code)
```

### Pattern 4: MCP Tool Integration

```javascript
// Create sandbox with MCP servers
const sandbox = await Sandbox.create({
    mcp: {
        github: { githubPersonalAccessToken: process.env.GITHUB_TOKEN },
        slack: { botToken: process.env.SLACK_BOT_TOKEN }
    }
})

// Connect MCP client
const client = new Client({ name: 'app', version: '1.0.0' })
const transport = new StreamableHTTPClientTransport(
    new URL(sandbox.getMcpUrl()),
    { requestInit: { headers: { 'Authorization': `Bearer ${await sandbox.getMcpToken()}` }}}
)
await client.connect(transport)

// List available tools
const tools = await client.listTools()
```

## Environment Variables

Required environment variable:
```bash
E2B_API_KEY=e2b_***
```

Get your API key from: https://e2b.dev/dashboard?tab=keys

## SDK Installation

```bash
# Python
pip install e2b-code-interpreter

# JavaScript/TypeScript
npm i @e2b/code-interpreter
```

## API Differences: Python vs JavaScript

| Operation | Python | JavaScript |
|-----------|--------|------------|
| Create | `Sandbox.create()` | `await Sandbox.create()` |
| Set timeout | `sandbox.set_timeout(60)` | `await sandbox.setTimeout(60000)` (milliseconds) |
| Get info | `sandbox.get_info()` | `await sandbox.getInfo()` |
| Run code | `sandbox.run_code(code)` | `await sandbox.runCode(code)` |
| Run command | `sandbox.commands.run(cmd)` | `await sandbox.commands.run(cmd)` |
| Get metrics | `sandbox.get_metrics()` | `await sandbox.getMetrics()` |
| List sandboxes | `Sandbox.list()` | `Sandbox.list()` |
| Connect | `Sandbox.connect(id)` | `await Sandbox.connect(id)` |
| Kill | `sandbox.kill()` | `await sandbox.kill()` |
| Pause | `sandbox.beta_pause()` | `await sandbox.betaPause()` |

## Troubleshooting

### Sandbox Times Out Too Quickly
- Increase timeout on creation: `Sandbox.create(timeout=300)`
- Or reset during runtime: `sandbox.set_timeout(300)`

### Code Execution Fails
- Check `execution.error` for details
- Verify file paths are absolute
- Ensure required packages are available
- Check language parameter matches code type

### Files Not Found
- Use absolute paths: `/home/user/filename`
- Verify file was uploaded successfully
- Check file exists: `sandbox.files.list('/home/user')`

### Persistence Issues
- Sandboxes auto-delete after 30 days
- Check sandbox still exists before connecting
- Handle `NotFoundException` when connecting

### High Resource Usage
- Check metrics: `sandbox.get_metrics()`
- Kill unused sandboxes
- Use smaller datasets or optimize code

### MCP Connection Issues
- Verify API keys for MCP servers
- Check MCP URL and token are valid
- Use MCP Inspector for debugging: `npx @modelcontextprotocol/inspector`

## Reference Documentation

For detailed API documentation and additional examples:
- [E2B Documentation](https://e2b.dev/docs)
- [Quickstart Guide](docs/quickstart.md)
- [Sandbox Lifecycle](docs/sandbox-lifecycle.md)
- [Monitoring & Events](docs/monitoring-and-events.md)
- [Advanced Sandbox Management](docs/advanced-sandbox.md)
- [File Operations](docs/filesystem.md)
- [MCP Gateway](docs/mcp-gateway.md)
- [Custom Templates](docs/custom-templates.md)
- [Persistence Guide](docs/persistence.md)