AIO Sandbox from Agent-Infra packages everything an AI agent needs to operate — browser, shell, filesystem, MCP server, VSCode, and Jupyter — into a single Docker container. Here’s how to get it running in under 5 minutes.

Prerequisites

  • Docker installed and running (get Docker)
  • Port 8080 available on your machine
  • ~2GB free disk space for the container image

Step 1: Pull and Run the Container

docker run --security-opt seccomp=unconfined --rm -it -p 8080:8080 ghcr.io/agent-infra/sandbox:latest

The --security-opt seccomp=unconfined flag is required for browser automation to work inside the container. The first run will pull the image (~1-2GB), subsequent starts are fast.

For a pinned production version (recommended — don’t use latest in CI/CD):

docker run --security-opt seccomp=unconfined --rm -it -p 8080:8080 ghcr.io/agent-infra/sandbox:1.0.0.150

Step 2: Verify Everything Is Up

Once running, open a browser and visit these endpoints to confirm each component is healthy:

Component URL
API docs http://localhost:8080/v1/docs
VNC browser http://localhost:8080/vnc/index.html?autoconnect=true
VSCode Server http://localhost:8080/code-server/
MCP services http://localhost:8080/mcp

If the VNC browser loads (you’ll see a Chromium window), everything is working.

Step 3: Connect Your Agent via MCP

If your agent framework supports MCP (OpenClaw, LangGraph, AutoGen, etc.), point it at:

http://localhost:8080/mcp

This single endpoint exposes all sandbox capabilities as MCP tools: browser navigation, shell execution, file read/write, and more. No additional configuration required.

Example with OpenClaw — add this to your MCP server config:

{
  "mcpServers": {
    "aio-sandbox": {
      "url": "http://localhost:8080/mcp"
    }
  }
}

Your agent can now call browser navigation, shell commands, and file operations through standard MCP tool calls.

Step 4: Install the Python or Node.js Client (Optional)

For programmatic control from your agent code, install the client library:

# Python
pip install agent-sandbox

# Node.js
npm install @agent-infra/sandbox

These clients wrap the REST API and provide typed interfaces for browser, shell, and file operations.

Python quick example:

from agent_sandbox import SandboxClient

client = SandboxClient("http://localhost:8080")

# Run a shell command
result = client.shell.run("echo hello from sandbox")
print(result.stdout)  # "hello from sandbox"

# Navigate browser and get page content
page = client.browser.navigate("https://example.com")
print(page.content[:200])

Step 5: Persist Data Between Runs (Optional)

By default the container is ephemeral (--rm flag removes it on exit). To persist files across runs, mount a volume:

docker run --security-opt seccomp=unconfined -it -p 8080:8080 \
  -v /your/local/workspace:/workspace \
  ghcr.io/agent-infra/sandbox:latest

Files written to /workspace inside the container will persist on your host at /your/local/workspace.

Troubleshooting

Container starts but VNC browser is blank:

  • Wait 15–20 seconds for Chromium to initialize inside the container
  • Refresh the VNC page

Port 8080 already in use:

  • Change the host port: -p 9090:8080 (then access everything at port 9090 instead)

seccomp errors on Docker Desktop:

  • Ensure Docker Desktop is updated to the latest version
  • On some systems: --security-opt seccomp=unconfined may not be needed; try removing it

Agent MCP calls failing:

  • Verify the container is running: docker ps
  • Check logs: docker logs [container_id]
  • Ensure your agent is using the correct MCP endpoint URL

What’s Next

With AIO Sandbox running, you have a full agentic execution environment wired to MCP. From here:

  • Browse the API documentation to see all available tool calls
  • Check the GitHub repository for deployment guides and advanced configuration
  • Follow Agent-Infra for updates — the project is actively maintained with regular releases

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260329-2000

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