---
title: Tabstack for the OpenAI Agents SDK | Tabstack
description: Give your OpenAI Agents SDK agents reliable web access with @tabstack/openai-agents: schema-enforced extraction, research, generation, and browser automation as native Agents SDK tools.
---

[`@tabstack/openai-agents`](https://www.npmjs.com/package/@tabstack/openai-agents) gives your [OpenAI Agents SDK](https://openai.github.io/openai-agents-js/) agents reliable web access: schema-enforced extraction, multi-source research, AI transformation, and browser automation, all as native Agents SDK tools backed by the official [`@tabstack/sdk`](https://www.npmjs.com/package/@tabstack/sdk).

## Install

- [npm](#tab-panel-248)
- [pnpm](#tab-panel-249)
- [yarn](#tab-panel-250)

Terminal window

```
npm install @tabstack/openai-agents @openai/agents zod
```

Terminal window

```
pnpm add @tabstack/openai-agents @openai/agents zod
```

Terminal window

```
yarn add @tabstack/openai-agents @openai/agents zod
```

`@openai/agents` (v0.13 or later) and `zod` are peer dependencies.

Zod 4 is required: the Agents SDK depends on it, and the adapter uses Zod 4’s native `z.toJSONSchema` to advertise each tool’s parameters.

The agent loop calls OpenAI, so `OPENAI_API_KEY` must be set alongside your Tabstack key.

## Create and Setup Your API Key

Before you can start using Tabstack API, you’ll need to create an API key and set it up in your environment.

### 1. Create Your API Key

1. Visit the [Tabstack Console](https://console.tabstack.ai/)
2. Sign in to your account (or create one if you haven’t already)
3. Navigate to the API Keys section and click the “Manage API Keys”
4. Once you are on the API Keys page, Click “Create New API Key”
5. Give your key a descriptive name (e.g., “Development”, “Production”) and click the “Create API Key”
6. Copy the generated API key and store it securely

Your API key will only be shown once. Make sure to copy and store it in a secure location.

### 2. Set Up Environment Variable

For security and convenience, we recommend storing your API key as an environment variable rather than hardcoding it in your scripts.

macOS/Linux

Terminal window

```
# Add to your shell profile (~/.bashrc, ~/.zshrc, or ~/.bash_profile)
export TABSTACK_API_KEY="your_api_key_here"


# Or set it temporarily for the current session
export TABSTACK_API_KEY="your_api_key_here"


# Reload your shell or run:
source ~/.bashrc  # or ~/.zshrc
```

Windows (Command Prompt)

```
# Set temporarily for current session
set TABSTACK_API_KEY=your_api_key_here


# Set permanently (requires restart)
setx TABSTACK_API_KEY "your_api_key_here"
```

Windows (PowerShell)

```
# Set temporarily for current session
$env:TABSTACK_API_KEY = "your_api_key_here"


# Set permanently for current user
[Environment]::SetEnvironmentVariable("TABSTACK_API_KEY", "your_api_key_here", "User")
```

### 3. Verify Your Setup

Test that your environment variable is set correctly:

**macOS/Linux/Windows (Git Bash):**

Terminal window

```
echo $TABSTACK_API_KEY
```

**Windows (Command Prompt):**

Terminal window

```
echo %TABSTACK_API_KEY%
```

**Windows (PowerShell):**

Terminal window

```
echo $env:TABSTACK_API_KEY
```

You should see your API key printed in the terminal.

## Quickstart

```
import { Agent, run } from "@openai/agents";
import { tabstackTools } from "@tabstack/openai-agents";


const agent = new Agent({
  name: "Research assistant",
  instructions:
    "You are a research assistant with web intelligence tools. Use research_question for open " +
    "questions that need multiple sources, extract_page_content to read a specific URL as " +
    "markdown, and the extract tools to pull structured fields from a page. Always cite sources.",
  tools: tabstackTools,
});


const result = await run(agent, "What are Vercel's pricing plans, with sources?");
console.log(result.finalOutput);
```

`tabstackTools` is an array of ready-to-use tools that resolves `TABSTACK_API_KEY` lazily on first call, so importing the package never requires a key to be set.

## The tools

| Tool                       | Export                       | What it does                                                      |
| -------------------------- | ---------------------------- | ----------------------------------------------------------------- |
| `extract_structured_data`  | `extractStructuredDataTool`  | Pull specific fields from a URL into a JSON shape you define.     |
| `extract_page_content`     | `extractPageContentTool`     | Fetch a page as clean markdown.                                   |
| `research_question`        | `researchQuestionTool`       | Synthesize a cited answer across multiple pages.                  |
| `generate_structured_data` | `generateStructuredDataTool` | Fetch a page, then AI-transform it into derived or reshaped JSON. |
| `automate_browser_task`    | `automateBrowserTaskTool`    | Run a multi-step, natural-language browser task.                  |

Import individual tools for a subset, or use the `tabstackTools` array for all of them:

```
import { Agent } from "@openai/agents";
import { extractPageContentTool, researchQuestionTool } from "@tabstack/openai-agents";


const agent = new Agent({
  name: "Research assistant",
  instructions: "Summarize pages and research questions.",
  tools: [researchQuestionTool, extractPageContentTool],
});
```

### Tool inputs

The model fills these in, but it helps to know the shapes:

- `extract_structured_data`: `url`, `json_schema_json` (a JSON-encoded JSON Schema string).
- `extract_page_content`: `url`.
- `research_question`: `query`.
- `generate_structured_data`: `url`, `instructions`, `json_schema_json`.
- `automate_browser_task`: `task`, plus optional `url`, `guardrails`, `data`, `country`, `max_iterations`, `max_validation_attempts`.

See [Schema design](/guides/schema-design/index.md) for writing `json_schema_json` that extracts reliably.

## Optional inputs

The model can pass these for finer control; they are sent to Tabstack only when present.

- `extract_structured_data`, `extract_page_content`, `generate_structured_data`:

  - `effort`: `"min"`, `"standard"`, or `"max"`. Use `"max"` for JS-heavy pages. See [Effort levels](/guides/effort-levels/index.md).
  - `nocache`: bypass the cache.
  - `country`: ISO 3166-1 alpha-2 code for [geotargeting](/guides/geotargeting/index.md).

- `research_question`: `mode` (`"fast"` or `"balanced"`), `nocache`.

- `automate_browser_task`: `guardrails` (constraints on what the agent may do), `data` (context for form filling), `country`, `max_iterations`, `max_validation_attempts`.

## Strict mode and schemas

The Agents SDK forces **strict** JSON Schema mode whenever a tool’s `parameters` is a Zod schema, and passing `strict: false` alongside a Zod schema throws. Strict mode cannot represent two constructs these tools rely on:

- optional fields (strict mode requires every property to appear in `required`), and
- `automate_browser_task`’s open `data` object, which needs a schema-valued `additionalProperties` that strict mode forbids.

So the adapter converts each schema to a JSON Schema and registers the tools with `strict: false`. The model still sees full field descriptions, and every call is validated inside `execute` before the request runs, so malformed model output fails fast with a clear error.

## Configuration

For a custom API key or base URL, or to reuse one client, build the tools explicitly:

```
import { createTabstackOpenAIAgentsTools } from "@tabstack/openai-agents";


const tools = createTabstackOpenAIAgentsTools({ apiKey: process.env.MY_KEY });
// or pass an SDK client you already have: createTabstackOpenAIAgentsTools({ client })
```

## Error handling

When a tool call fails it throws `TabstackToolError` (a normalized message plus an HTTP `status` for API errors). The Agents SDK catches tool errors and surfaces them to the model as a tool result, so a failing call does not abort the run by default.

## Related

- [Integrations overview](/integrations/index.md)
- [Tabstack TypeScript SDK](/sdks/typescript/quickstart/index.md)
- [Schema design](/guides/schema-design/index.md)
- [Claude Agent SDK integration](/integrations/claude-agent/index.md) and [Vercel AI SDK integration](/integrations/vercel-ai/index.md)