diff --git a/docs/guide/integrations/index.md b/docs/guide/integrations/index.md
index 0ab7b9d6c..54b94102a 100644
--- a/docs/guide/integrations/index.md
+++ b/docs/guide/integrations/index.md
@@ -51,3 +51,4 @@ lang: en-US
 | [Claude Code Integration Guide](./claude-code.md) | shsaihdsaiudh | 2026-07-06 | integration, claude-code, coding-agent |
 | [LangChain Integration Guide](./langchain.md) | peerless-hero | 2026-07-07 | integration, langchain, agent |
 | [Tigris Volume Integration Guide](./tigris.md) | davidmyriel | 2026-07-31 | integration, tigris, volume, storage, s3 |
+| [OpenAI Agents SDK Integration Guide](./openai-agents-sdk.md) | ZedingZhang | 2026-08-19 | integration, openai-agents-sdk, agent |
diff --git a/docs/guide/integrations/openai-agents-sdk.md b/docs/guide/integrations/openai-agents-sdk.md
new file mode 100644
index 000000000..290dae76d
--- /dev/null
+++ b/docs/guide/integrations/openai-agents-sdk.md
@@ -0,0 +1,238 @@
+---
+title: OpenAI Agents SDK Integration Guide
+author: ZedingZhang
+date: 2026-08-19
+tags:
+  - integration
+  - openai-agents-sdk
+  - agent
+lang: en-US
+---
+
+# OpenAI Agents SDK Integration Guide
+
+[中文](../../zh/guide/integrations/openai-agents-sdk.md)
+
+Use a CubeSandbox MicroVM as the sandbox execution environment for an
+[OpenAI Agents SDK](https://developers.openai.com/api/docs/guides/agents/sandboxes)
+`SandboxAgent`. CubeSandbox exposes an E2B-compatible API, so the SDK's built-in
+`E2BSandboxClient` can provide the sandbox execution plane without a custom
+provider implementation.
+
+This page is the short integration entry point. The repository already ships
+complete Shell Agent, SWE-bench, pause/resume, and Code Interpreter examples;
+the links below let you run and inspect those implementations directly.
+
+## Integration Target and Version
+
+| Component | Baseline used by the bundled examples |
+| --- | --- |
+| OpenAI Agents SDK | Python package `openai-agents[e2b]` with Sandbox Agents support |
+| Python | 3.10+ |
+| CubeSandbox | E2B-compatible CubeAPI and a reachable CubeProxy data plane |
+| Sandbox modes | Generic E2B (`E2BSandboxType.E2B`) and Code Interpreter (`E2BSandboxType.CODE_INTERPRETER`) |
+
+Sandbox Agents are currently beta in the OpenAI Agents SDK. The example
+requirements intentionally install the current SDK release; pin the resolved
+versions after validating them for a production deployment.
+
+## Prerequisites
+
+- A running [CubeSandbox deployment](/guide/quickstart) with CubeAPI reachable,
+  normally at `http://<cube-host>:3000`.
+- `cubemastercli` connected to the cluster and a sandbox template ID.
+- Python 3.10+ on the machine running the Agent harness.
+- An API key and model name for TokenHub or another OpenAI-compatible LLM
+  endpoint when running the full Agent demo.
+
+::: warning Control plane and data plane
+`E2B_API_URL` selects the CubeAPI control-plane endpoint. The official E2B SDK
+also connects to per-sandbox data-plane hostnames. A one-click local deployment
+includes CoreDNS; production deployments should configure wildcard DNS. If you
+must use the official E2B SDK locally without wildcard DNS, use the
+[E2B development sidecar](/guide/connect-existing-cluster).
+:::
+
+## Setup
+
+### 1. Choose a CubeSandbox template
+
+`simple_demo.py` works with any Linux template that runs envd on port `49983`.
+You can reuse an existing template or create the SWE-bench template used by the
+bundled debugging demo:
+
+```bash
+cubemastercli tpl create-from-image \
+  --image cube-sandbox-image.tencentcloudcr.com/demo/django_1776_django-13447:latest \
+  --writable-layer-size 1G \
+  --expose-port 49983 \
+  --cpu 4000 --memory 8192 \
+  --probe 49983
+```
+
+The command starts an asynchronous build. Use the job ID from its output to
+monitor the build:
+
+```bash
+cubemastercli tpl watch --job-id <job_id>
+```
+
+Wait until the status becomes `READY`, then copy the `template_id` from the
+output.
+
+### 2. Install the example dependencies
+
+```bash
+cd examples/openai-agents-example
+python3 -m venv .venv
+source .venv/bin/activate
+pip install -r requirements.txt
+cp .env.example .env
+```
+
+Configure `.env`:
+
+| Variable | Purpose |
+| --- | --- |
+| `E2B_API_URL` | CubeAPI control-plane URL, for example `http://<cube-host>:3000` |
+| `E2B_API_KEY` | Required by the E2B SDK; use the `e2b_`-prefixed key accepted by your CubeAPI auth callback, or `e2b_000000` when authentication is disabled |
+| `CUBE_TEMPLATE_ID` | CubeSandbox template ID |
+| `TOKENHUB_API_KEY` | TokenHub key used by the bundled demos |
+| `OPENAI_API_KEY` / `OPENAI_BASE_URL` | Alternative OpenAI-compatible LLM credentials and endpoint |
+| `CUBE_SSL_CERT_FILE` | Optional CubeSandbox CA bundle for a self-signed deployment |
+
+Use a model name that exists at the configured LLM endpoint. The template
+variable is application-owned: an existing E2B application can keep its current
+variable name, while the bundled examples use `CUBE_TEMPLATE_ID` for clarity.
+
+## Integration Snippet
+
+Keep the Agent definition and replace only its sandbox connection settings:
+
+```python
+import asyncio
+import os
+
+from agents import Runner
+from agents.run import RunConfig
+from agents.sandbox import SandboxRunConfig
+from agents.extensions.sandbox import (
+    E2BSandboxClient,
+    E2BSandboxClientOptions,
+    E2BSandboxType,
+)
+
+async def main():
+    run_config = RunConfig(
+        sandbox=SandboxRunConfig(
+            client=E2BSandboxClient(),
+            options=E2BSandboxClientOptions(
+                sandbox_type=E2BSandboxType.E2B,
+                template=os.environ["CUBE_TEMPLATE_ID"],
+                timeout=300,
+            ),
+        ),
+        workflow_name="Cube shell agent",
+    )
+
+    result = await Runner.run(
+        agent,
+        "What OS is running? Show uname and /etc/os-release.",
+        run_config=run_config,
+    )
+    print(result.final_output)
+
+
+# `agent` is your existing SandboxAgent.
+asyncio.run(main())
+```
+
+The checked-in [`simple_demo.py`](https://github.com/TencentCloud/CubeSandbox/blob/master/examples/openai-agents-example/simple_demo.py)
+adds a complete `SandboxAgent`, model configuration, cleanup, and the current
+CubeSandbox envd compatibility handling around this core snippet.
+
+### Migrating an existing E2B-backed Agent
+
+The client class does not change. Point the existing E2B configuration at Cube
+and provide a Cube template ID:
+
+```diff
+- E2B_API_URL="https://api.e2b.dev"
+- E2B_API_KEY="<e2b-cloud-key>"
+- SANDBOX_TEMPLATE="<e2b-template>"
++ E2B_API_URL="http://<cube-host>:3000"
++ E2B_API_KEY="e2b_000000"
++ SANDBOX_TEMPLATE="<cube-template-id>"
+```
+
+The example uses `e2b_000000` for a deployment with CubeAPI authentication
+disabled. If authentication is enabled, replace it with the `e2b_`-prefixed
+credential accepted by your auth callback.
+
+`SANDBOX_TEMPLATE` represents whatever environment variable your application
+already passes to `E2BSandboxClientOptions(template=...)`; it does not need to
+be renamed.
+
+## Runnable Demo
+
+First verify the sandbox path without making an LLM request:
+
+```bash
+cd examples/openai-agents-example
+python main.py --sandbox-only --timeout 60
+```
+
+Verify that filesystem state survives a pause/resume cycle:
+
+```bash
+python simple_demo.py --pause-resume
+```
+
+Then run the Shell Agent against a real task:
+
+```bash
+python simple_demo.py \
+  --question "What OS is running? Show uname and the first 3 lines of /etc/os-release."
+```
+
+For a larger workflow, `main.py` lets the Agent inspect a Django source tree and
+analyze the SWE-bench `django__django-13447` bug. See the bilingual
+[example README](https://github.com/TencentCloud/CubeSandbox/tree/master/examples/openai-agents-example)
+for its arguments and expected flow.
+
+## Going Further
+
+- **Longer runs:** set both the sandbox lifetime in
+  `E2BSandboxClientOptions(timeout=...)` and an appropriate Agent turn limit.
+- **Pause and resume:** set `pause_on_exit=True`, retain the session state, and
+  call `E2BSandboxClient.resume(...)`. The bundled pause/resume demo performs a
+  complete write, pause, resume, read, and cleanup cycle.
+- **Code Interpreter:** use the
+  [`openai-agents-code-interpreter`](https://github.com/TencentCloud/CubeSandbox/tree/master/examples/openai-agents-code-interpreter)
+  examples. Generic execution needs envd on `49983`; Jupyter mode additionally
+  needs the Code Interpreter service on `49999` in the template image.
+- **Network and storage controls:** configure Cube-specific policies through
+  [network policy](/guide/network-policy), [security proxy](/guide/security-proxy),
+  and [persistent storage](/guide/persistent-storage). Features not represented
+  by the E2B compatibility surface can be prepared in the template or managed
+  through CubeSandbox's native APIs.
+
+## Caveats
+
+- The bundled scripts set the E2B envd username to `root` and remove the `stdin`
+  argument when talking to older envd versions. Copy the compatibility block
+  from the runnable example if your deployment requires it.
+- `E2B_API_URL` alone does not replace data-plane DNS or sidecar configuration;
+  verify both CubeAPI and CubeProxy reachability.
+- `E2BSandboxType.CODE_INTERPRETER` requires a purpose-built template. Selecting
+  that enum does not install or start Jupyter automatically.
+- Treat the sandbox as untrusted execution. Keep LLM credentials in the Agent
+  harness unless the task explicitly needs them inside the MicroVM.
+
+## References
+
+- [OpenAI Sandbox Agents documentation](https://developers.openai.com/api/docs/guides/agents/sandboxes)
+- [Runnable Shell Agent and SWE-bench examples](https://github.com/TencentCloud/CubeSandbox/tree/master/examples/openai-agents-example)
+- [Runnable Code Interpreter examples](https://github.com/TencentCloud/CubeSandbox/tree/master/examples/openai-agents-code-interpreter)
+- [Detailed OpenAI Agents SDK × CubeSandbox implementation notes](https://github.com/TencentCloud/CubeSandbox/blob/master/examples/openai-agents-example/openai-agents-sandbox-cube-integration.md)
+- [Connecting to an existing CubeSandbox cluster](/guide/connect-existing-cluster)
diff --git a/docs/zh/guide/integrations/index.md b/docs/zh/guide/integrations/index.md
index 72695d9d2..fd6d37a32 100644
--- a/docs/zh/guide/integrations/index.md
+++ b/docs/zh/guide/integrations/index.md
@@ -51,3 +51,4 @@ lang: zh-CN
 | [Claude Code 集成指南](./claude-code.md) | shsaihdsaiudh | 2026-07-06 | integration, claude-code, coding-agent |
 | [LangChain 集成指南](./langchain.md) | peerless-hero | 2026-07-07 | integration, langchain, agent |
 | [Tigris Volume 集成指南](./tigris.md) | davidmyriel | 2026-07-31 | integration, tigris, volume, storage, s3 |
+| [OpenAI Agents SDK 集成指南](./openai-agents-sdk.md) | ZedingZhang | 2026-08-19 | integration, openai-agents-sdk, agent |
diff --git a/docs/zh/guide/integrations/openai-agents-sdk.md b/docs/zh/guide/integrations/openai-agents-sdk.md
new file mode 100644
index 000000000..be1581025
--- /dev/null
+++ b/docs/zh/guide/integrations/openai-agents-sdk.md
@@ -0,0 +1,219 @@
+---
+title: OpenAI Agents SDK 集成指南
+author: ZedingZhang
+date: 2026-08-19
+tags:
+  - integration
+  - openai-agents-sdk
+  - agent
+lang: zh-CN
+---
+
+# OpenAI Agents SDK 集成指南
+
+[English](../../../guide/integrations/openai-agents-sdk.md)
+
+让 [OpenAI Agents SDK](https://developers.openai.com/api/docs/guides/agents/sandboxes) 的
+`SandboxAgent` 使用 CubeSandbox MicroVM 作为沙箱执行环境。CubeSandbox 暴露 E2B 兼容 API，
+因此可以直接复用 SDK 内置的 `E2BSandboxClient` 作为沙箱执行平面，无需实现自定义 provider。
+
+本文是一份简明的集成入口。仓库已经提供完整的 Shell Agent、SWE-bench、暂停/恢复和 Code
+Interpreter 示例；下方链接可以直接运行并查看这些实现。
+
+## 集成对象与版本
+
+| 组件 | 仓库示例使用的基线 |
+| --- | --- |
+| OpenAI Agents SDK | 带 Sandbox Agents 支持的 Python 包 `openai-agents[e2b]` |
+| Python | 3.10+ |
+| CubeSandbox | E2B 兼容 CubeAPI，以及可访问的 CubeProxy 数据平面 |
+| 沙箱模式 | 通用 E2B（`E2BSandboxType.E2B`）和 Code Interpreter（`E2BSandboxType.CODE_INTERPRETER`） |
+
+OpenAI Agents SDK 的 Sandbox Agents 目前处于 beta。示例 requirements 有意安装当前 SDK
+版本；生产部署应在完成验证后锁定解析出的依赖版本。
+
+## 前置条件
+
+- 已运行的 [CubeSandbox 部署](/zh/guide/quickstart)，并且可以访问 CubeAPI，通常为
+  `http://<cube-host>:3000`。
+- `cubemastercli` 已连接集群，并已获得一个沙箱模板 ID。
+- 运行 Agent harness 的主机安装了 Python 3.10+。
+- 运行完整 Agent demo 时，需要 TokenHub 或其他 OpenAI 兼容 LLM 端点的 API Key 和模型名。
+
+::: warning 控制平面与数据平面
+`E2B_API_URL` 用于选择 CubeAPI 控制平面端点。官方 E2B SDK 还会访问每个沙箱的数据平面域名。
+一键本地部署自带 CoreDNS；生产环境应配置泛域名 DNS。若必须在没有泛域名 DNS 的本地环境中
+使用官方 E2B SDK，请使用 [E2B 开发 sidecar](/zh/guide/connect-existing-cluster)。
+:::
+
+## 安装与配置
+
+### 1. 选择 CubeSandbox 模板
+
+`simple_demo.py` 可以使用任何在 `49983` 端口运行 envd 的 Linux 模板。你可以复用已有模板，
+也可以创建仓库调试 demo 使用的 SWE-bench 模板：
+
+```bash
+cubemastercli tpl create-from-image \
+  --image cube-sandbox-image.tencentcloudcr.com/demo/django_1776_django-13447:latest \
+  --writable-layer-size 1G \
+  --expose-port 49983 \
+  --cpu 4000 --memory 8192 \
+  --probe 49983
+```
+
+该命令会异步构建模板。使用输出中的任务 ID 监控构建进度：
+
+```bash
+cubemastercli tpl watch --job-id <job_id>
+```
+
+等待状态变为 `READY`，然后记录输出中的 `template_id`。
+
+### 2. 安装示例依赖
+
+```bash
+cd examples/openai-agents-example
+python3 -m venv .venv
+source .venv/bin/activate
+pip install -r requirements.txt
+cp .env.example .env
+```
+
+配置 `.env`：
+
+| 变量 | 用途 |
+| --- | --- |
+| `E2B_API_URL` | CubeAPI 控制平面地址，例如 `http://<cube-host>:3000` |
+| `E2B_API_KEY` | E2B SDK 必填；开启 CubeAPI 鉴权时使用鉴权回调接受的 `e2b_` 前缀 Key，未开启时使用 `e2b_000000` |
+| `CUBE_TEMPLATE_ID` | CubeSandbox 模板 ID |
+| `TOKENHUB_API_KEY` | 仓库 demo 默认使用的 TokenHub Key |
+| `OPENAI_API_KEY` / `OPENAI_BASE_URL` | 其他 OpenAI 兼容 LLM 的凭据和端点 |
+| `CUBE_SSL_CERT_FILE` | 可选，自签名 CubeSandbox 部署的 CA bundle |
+
+模型名必须存在于配置的 LLM 端点。模板变量名由应用自行决定：现有 E2B 应用可以保留原变量名，
+仓库示例为了清晰使用 `CUBE_TEMPLATE_ID`。
+
+## 集成代码片段
+
+保留原有 Agent 定义，只替换沙箱连接配置：
+
+```python
+import asyncio
+import os
+
+from agents import Runner
+from agents.run import RunConfig
+from agents.sandbox import SandboxRunConfig
+from agents.extensions.sandbox import (
+    E2BSandboxClient,
+    E2BSandboxClientOptions,
+    E2BSandboxType,
+)
+
+async def main():
+    run_config = RunConfig(
+        sandbox=SandboxRunConfig(
+            client=E2BSandboxClient(),
+            options=E2BSandboxClientOptions(
+                sandbox_type=E2BSandboxType.E2B,
+                template=os.environ["CUBE_TEMPLATE_ID"],
+                timeout=300,
+            ),
+        ),
+        workflow_name="Cube shell agent",
+    )
+
+    result = await Runner.run(
+        agent,
+        "What OS is running? Show uname and /etc/os-release.",
+        run_config=run_config,
+    )
+    print(result.final_output)
+
+
+# `agent` 是已有的 SandboxAgent。
+asyncio.run(main())
+```
+
+仓库中的 [`simple_demo.py`](https://github.com/TencentCloud/CubeSandbox/blob/master/examples/openai-agents-example/simple_demo.py)
+在这段核心配置之外补齐了完整的 `SandboxAgent`、模型配置、资源清理，以及当前 CubeSandbox envd
+所需的兼容处理。
+
+### 迁移已有的 E2B Agent
+
+客户端类无需更换。只需把现有 E2B 配置指向 Cube，并传入 Cube 模板 ID：
+
+```diff
+- E2B_API_URL="https://api.e2b.dev"
+- E2B_API_KEY="<e2b-cloud-key>"
+- SANDBOX_TEMPLATE="<e2b-template>"
++ E2B_API_URL="http://<cube-host>:3000"
++ E2B_API_KEY="e2b_000000"
++ SANDBOX_TEMPLATE="<cube-template-id>"
+```
+
+上例适用于未开启 CubeAPI 鉴权的部署。如果已经开启鉴权，请把 `e2b_000000` 替换为鉴权回调
+接受的 `e2b_` 前缀凭据。
+
+`SANDBOX_TEMPLATE` 代表应用原先传给 `E2BSandboxClientOptions(template=...)` 的环境变量，
+无需特意改名。
+
+## 可运行 Demo
+
+先在不请求 LLM 的情况下验证沙箱链路：
+
+```bash
+cd examples/openai-agents-example
+python main.py --sandbox-only --timeout 60
+```
+
+验证文件系统状态能否跨暂停/恢复保留：
+
+```bash
+python simple_demo.py --pause-resume
+```
+
+然后让 Shell Agent 执行一个真实任务：
+
+```bash
+python simple_demo.py \
+  --question "What OS is running? Show uname and the first 3 lines of /etc/os-release."
+```
+
+对于更完整的工作流，`main.py` 会让 Agent 检查 Django 源码并分析 SWE-bench 的
+`django__django-13447` Bug。参数和预期流程见双语
+[示例 README](https://github.com/TencentCloud/CubeSandbox/tree/master/examples/openai-agents-example)。
+
+## 进阶用法
+
+- **长任务：**同时设置 `E2BSandboxClientOptions(timeout=...)` 的沙箱生命周期，以及合适的
+  Agent 最大轮数。
+- **暂停与恢复：**设置 `pause_on_exit=True`，保留会话状态，然后调用
+  `E2BSandboxClient.resume(...)`。仓库 demo 完整执行了写入、暂停、恢复、读取和清理流程。
+- **Code Interpreter：**使用
+  [`openai-agents-code-interpreter`](https://github.com/TencentCloud/CubeSandbox/tree/master/examples/openai-agents-code-interpreter)
+  中的示例。通用执行需要 `49983` 端口的 envd；Jupyter 模式还要求模板镜像在 `49999`
+  端口提供 Code Interpreter 服务。
+- **网络与存储控制：**通过[网络策略](/zh/guide/network-policy)、
+  [安全代理](/zh/guide/security-proxy)和[持久化存储](/zh/guide/persistent-storage)配置 Cube
+  专有能力。E2B 兼容层未覆盖的能力可以预先写入模板，或通过 CubeSandbox 原生 API 管理。
+
+## 注意事项
+
+- 仓库示例把 E2B envd 用户设为 `root`，并在对接旧版 envd 时移除 `stdin` 参数。如果你的部署
+  仍需这些适配，请从可运行示例复制兼容代码块。
+- 仅配置 `E2B_API_URL` 不能替代数据平面的 DNS 或 sidecar 配置；需要同时验证 CubeAPI 和
+  CubeProxy 的可达性。
+- `E2BSandboxType.CODE_INTERPRETER` 需要专门构建的模板；选择该枚举不会自动安装或启动
+  Jupyter。
+- 应把沙箱视为不受信任的执行环境。除非任务明确需要，否则把 LLM 凭据保留在 Agent harness 中，
+  不要传入 MicroVM。
+
+## 参考资料
+
+- [OpenAI Sandbox Agents 官方文档](https://developers.openai.com/api/docs/guides/agents/sandboxes)
+- [可运行的 Shell Agent 与 SWE-bench 示例](https://github.com/TencentCloud/CubeSandbox/tree/master/examples/openai-agents-example)
+- [可运行的 Code Interpreter 示例](https://github.com/TencentCloud/CubeSandbox/tree/master/examples/openai-agents-code-interpreter)
+- [OpenAI Agents SDK × CubeSandbox 详细实现说明](https://github.com/TencentCloud/CubeSandbox/blob/master/examples/openai-agents-example/openai-agents-sandbox-cube-integration_zh.md)
+- [连接现有 CubeSandbox 集群](/zh/guide/connect-existing-cluster)