GitHub - TwillAI/agentbox-sdk: The open-source TypeScript...

Run coding agents inside sandboxes. One API, any provider.

Unlike wrappers that shell out to CLIs in non-interactive mode (e.g. claude --print), AgentBox launches each agent as a server process inside the sandbox and communicates over WebSocket or HTTP. This preserves the full interactive capabilities of each agent — approval flows, tool-use control, streaming events.

import { Agent, Sandbox } from "agentbox-sdk";

const sandbox = new Sandbox("local-docker", {
  workingDir: "/workspace",
  image: process.env.IMAGE_ID!,
  env: { ANTHROPIC_API_KEY: process.env.ANTHROPIC_API_KEY! },
});

const run = new Agent("claude-code", {
  sandbox,
  cwd: "/workspace",
  approvalMode: "auto",
}).stream({
  model: "sonnet",
  input: "Create a hello world Express server in /workspace/server.ts",
});

for await (const event of run) {
  if (event.type === "text.delta") process.stdout.write(event.delta);
}

await sandbox.delete();

Providers are mix-and-match:

Agents — claude-code, opencode, codex
Sandboxes — local-docker, e2b, modal, daytona, vercel

Swap either one and your app code stays the same.

Install

npm install agentbox-sdk

Requires Node >= 20. The agent CLI you want to use (claude, opencode, codex) should be installed inside your sandbox image.

Getting started

1. Build a sandbox image

AgentBox ships with built-in image presets. Build one for your sandbox provider:

npx agentbox image build --provider local-docker --preset browser-agent

This prints an image reference (a Docker tag, Modal image ID, E2B template, or Daytona snapshot depending on the provider). Set it as IMAGE_ID:

export IMAGE_ID=<printed value>

2. Run an agent

import { Agent, Sandbox } from "agentbox-sdk";

const sandbox = new Sandbox("local-docker", {
  workingDir: "/workspace",
  image: process.env.IMAGE_ID!,
  env: { ANTHROPIC_API_KEY: process.env.ANTHROPIC_API_KEY! },
});

const agent = new Agent("claude-code", {
  sandbox,
  cwd: "/workspace",
  approvalMode: "auto",
});

const result = await agent.run({
  model: "sonnet",
  input:
    "Explain the project structure and write a summary to /workspace/OVERVIEW.md",
});

console.log(result.text);
await sandbox.delete();

3. Stream events

agent.stream() returns an async iterable of normalized events:

const run = agent.stream({
  model: "sonnet",
  input: "Write a fizzbuzz in Python",
});

for await (const event of run) {
  if (event.type === "text.delta") {
    process.stdout.write(event.delta);
  }
}

const result = await run.finished;

Agents

Three agent providers are supported. Each wraps a CLI that runs inside the sandbox:

Provider	CLI	Model format
`claude-code`	`claude`	`sonnet`, `opus`, `haiku`
`opencode`	`opencode`	`anthropic/claude-sonnet-4-6`, `openai/gpt-4.1`
`codex`	`codex`	`gpt-5.3-codex`, `gpt-5.4`

new Agent("claude-code", { sandbox, cwd: "/workspace", approvalMode: "auto" });
new Agent("opencode", { sandbox, cwd: "/workspace", approvalMode: "auto" });
new Agent("codex", { sandbox, cwd: "/workspace", approvalMode: "auto" });

Sandboxes

Five sandbox providers are supported. Each gives you an isolated environment with the same interface:

Provider	What it is	Auth
`local-docker`	Local Docker container	Docker daemon
`e2b`	Cloud micro-VM	`E2B_API_KEY`
`modal`	Cloud container	`MODAL_TOKEN_ID` + `MODAL_TOKEN_SECRET`
`daytona`	Cloud dev environment	`DAYTONA_API_KEY`
`vercel`	Ephemeral cloud VM	`VERCEL_TOKEN` + `VERCEL_TEAM_ID` + `VERCEL_PROJECT_ID`

Every sandbox supports: run(), runAsync(), gitClone(), openPort(), getPreviewLink(), snapshot(), stop(), delete().

Vercel sandboxes use runtime snapshots instead of pre-built images — call sandbox.snapshot() to capture state and pass the returned id via provider.snapshotId on the next run.

Vercel also requires ports to be declared at create time via provider.ports — openPort() is a no-op at runtime, so any port the agent (or your own code) will listen on must be listed up front:

const sandbox = new Sandbox("vercel", {
  provider: {
    snapshotId: process.env.VERCEL_SNAPSHOT_ID!,
    ports: [4096], // e.g. opencode; codex/claude-code use 43180
  },
});

Skills

Attach GitHub repos as agent skills. They're cloned into the sandbox and surfaced to the agent:

const agent = new Agent("claude-code", {
  sandbox,
  cwd: "/workspace",
  approvalMode: "auto",
  skills: [
    {
      name: "agent-browser",
      repo: "https://github.com/vercel-labs/agent-browser",
    },
  ],
});

You can also embed skills inline:

skills: [
  {
    source: "embedded",
    name: "lint-fix",
    files: {
      "SKILL.md": "Run `npm run lint:fix` and verify the output is clean.",
    },
  },
],

Sub-agents

Delegate tasks to specialized sub-agents:

const agent = new Agent("claude-code", {
  sandbox,
  cwd: "/workspace",
  approvalMode: "auto",
  subAgents: [
    {
      name: "reviewer",
      description: "Reviews code for bugs and security issues",
      instructions:
        "Flag bugs, security issues, and missing edge cases. Be concise.",
      tools: ["bash", "read"],
    },
  ],
});

MCP servers

Connect MCP servers to give agents access to external tools:

const agent = new Agent("claude-code", {
  sandbox,
  cwd: "/workspace",
  approvalMode: "auto",
  mcps: [
    {
      name: "filesystem",
      type: "local",
      command: "npx",
      args: ["-y", "@modelcontextprotocol/server-filesystem", "/workspace"],
    },
    {
      name: "my-api",
      type: "remote",
      url: "https://mcp.example.com/sse",
    },
  ],
});

Custom commands

const agent = new Agent("opencode", {
  sandbox,
  cwd: "/workspace",
  approvalMode: "auto",
  commands: [
    {
      name: "triage",
      description: "Triage a bug report into root cause + fix plan",
      template:
        "Analyze the bug report. Return: root cause, files to change, and tests to add.",
    },
  ],
});

Multimodal input

Pass images and files alongside text:

import { pathToFileURL } from "node:url";

const result = await agent.run({
  model: "sonnet",
  input: [
    { type: "text", text: "Describe this mockup and suggest improvements." },
    { type: "image", image: pathToFileURL("/workspace/mockup.png") },
  ],
});

Provider support: opencode (text, images, files), claude-code (text, images, PDFs), codex (text, images).

Custom sandbox images

Define your own image when the built-in presets don't cover your needs.

Create my-image.mjs:

export default {
  name: "playwright-sandbox",
  base: "node:20-bookworm",
  env: { PLAYWRIGHT_BROWSERS_PATH: "/ms-playwright" },
  run: [
    "apt-get update && apt-get install -y git python3 ca-certificates",
    "npm install -g pnpm @anthropic-ai/claude-code",
    "npx playwright install --with-deps chromium",
  ],
  workdir: "/workspace",
  cmd: ["sleep", "infinity"],
};

Build it:

npx agentbox image build --provider local-docker --file ./my-image.mjs

This works with all providers. For cloud providers, the printed value will be that provider's native image reference.

Hooks

Hooks let you run code at specific points in the agent lifecycle. Each provider has its own hook format:

Claude Code — native hook settings:

new Agent("claude-code", {
  sandbox,
  cwd: "/workspace",
  provider: {
    hooks: {
      PostToolUse: [
        { matcher: "Bash", hooks: [{ type: "command", command: "echo done" }] },
      ],
    },
  },
});

Codex — similar to Claude Code:

new Agent("codex", {
  sandbox,
  cwd: "/workspace",
  provider: {
    hooks: {
      PostToolUse: [
        { matcher: "Bash", hooks: [{ type: "command", command: "echo done" }] },
      ],
    },
  },
});

OpenCode — plugin-based hooks:

new Agent("opencode", {
  sandbox,
  cwd: "/workspace",
  provider: {
    plugins: [
      {
        name: "session-notifier",
        hooks: [{ event: "session.idle", body: 'return "session-idle";' }],
      },
    ],
  },
});

Examples

The examples/ directory has short, runnable scripts that each demonstrate one feature:

Example	What it shows
`basic.ts`	Minimal agent + sandbox
`streaming.ts`	Stream and handle events
`interactive-approval.ts`	Approve tool calls from stdin
`skills.ts`	Attach a GitHub skill
`sub-agents.ts`	Delegate to sub-agents
`mcp-server.ts`	Connect an MCP server
`multimodal.ts`	Send images to the agent
`custom-image.ts`	Build a custom sandbox image
`cloud-sandbox.ts`	Use E2B, Modal, or Daytona
`basic-vercel.ts`	Use a Vercel sandbox
`git-clone.ts`	Clone a repo into the sandbox

All examples import from "agentbox-sdk" like a normal dependency. Run them with:

npx tsx examples/basic.ts

Package exports

import { Agent, Sandbox } from "agentbox-sdk"; // main entrypoint
import type { AgentRun } from "agentbox-sdk/agents"; // agent types
import type { CommandResult } from "agentbox-sdk/sandboxes"; // sandbox types
import type { NormalizedAgentEvent } from "agentbox-sdk/events"; // event types

Contributing

npm install
npm run build
npm run typecheck
npm test

npm run build generates the dist/ directory. You need to build before the examples or CLI work locally.

To test your local build from another project:

npm run build && npm pack
# then in your project:
npm install /path/to/agentbox-sdk-0.1.0.tgz

Tests

npm test                                              # fast, no real providers
AGENTBOX_RUN_SMOKE_TESTS=1 npm run test:smoke         # live smoke tests
AGENTBOX_RUN_MATRIX_E2E=1 npm run test:e2e:matrix     # provider matrix

Live test suites are opt-in because they provision real infrastructure.

License

MIT

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