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AI SDK by Vercel - build apps like ChatGPT, Claude, Gemini, and more with a single interface for any model using the Vercel AI Gateway or go direct to OpenAI, Anthropic, Google, or any other model provider.
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---
title: DevTools
description: Debug and inspect AI SDK applications with DevTools
---
# DevTools
<Note type="warning">
AI SDK DevTools is intended for local development only. Do not use in
production environments.
</Note>
AI SDK DevTools gives you full visibility over your AI SDK calls with [`generateText`](/docs/reference/ai-sdk-core/generate-text), [`streamText`](/docs/reference/ai-sdk-core/stream-text), and [`ToolLoopAgent`](/docs/reference/ai-sdk-core/tool-loop-agent). It helps you debug and inspect LLM requests, responses, tool calls, and multi-step interactions through a web-based UI.
DevTools is composed of two parts:
1. **Telemetry Integration**: Captures runs and steps from your AI SDK calls via the [telemetry](/docs/ai-sdk-core/telemetry) system
2. **Viewer**: A web UI to inspect the captured data
## Installation
Install the DevTools package:
```bash
pnpm add @ai-sdk/devtools
```
## Requirements
- AI SDK v7 (`ai@latest`)
- Node.js compatible runtime
## Using DevTools
### Register the integration
Register `DevToolsTelemetry` globally so it captures all AI SDK calls:
```ts
import { registerTelemetry } from 'ai';
import { DevToolsTelemetry } from '@ai-sdk/devtools';
registerTelemetry(DevToolsTelemetry());
```
Telemetry is enabled automatically once an integration is registered — no per-call configuration is needed:
```ts
import { generateText } from 'ai';
const result = await generateText({
model: openai('gpt-4o'),
prompt: 'What cities are in the United States?',
});
```
You can also pass the integration to individual calls instead of registering it globally:
```ts highlight="7-9"
import { streamText } from 'ai';
import { DevToolsTelemetry } from '@ai-sdk/devtools';
const result = streamText({
model: openai('gpt-4o'),
prompt: 'Hello!',
telemetry: {
integrations: [DevToolsTelemetry()],
},
});
```
### Launch the viewer
Start the DevTools viewer:
```bash
npx @ai-sdk/devtools@latest
```
Open [http://localhost:4983](http://localhost:4983) to view your AI SDK interactions.
### Choose a viewer theme
The viewer uses the dark theme by default. Use the theme button in the viewer
header to switch between dark and light themes. Your selection is stored in
your browser and restored the next time you open the viewer at the same origin.
### Monorepo usage
If you are using a monorepo setup (e.g. Turborepo, Nx), start DevTools from the same workspace where your AI SDK code runs.
For example, if your API is in `apps/api`, run:
```bash
cd apps/api
npx @ai-sdk/devtools@latest
```
The explicit `@latest` tag ensures that `npx` installs an executable copy
instead of selecting a transitive dependency whose binary is not linked into
the workspace.
## Captured data
DevTools captures the following information from your AI SDK calls:
- **Input parameters and prompts**: View the complete input sent to your LLM
- **Output content and tool calls**: Inspect generated text and tool invocations
- **Token usage and timing**: Monitor resource consumption and performance
- **Raw provider data**: Access provider request and response payloads when body retention is enabled
Telemetry is enabled automatically, but AI SDK 7 excludes raw request and response bodies from step results by default. To make them available to DevTools for `generateText`, enable body retention on the call:
```ts highlight="4-7"
const result = await generateText({
model: openai('gpt-4o'),
prompt: 'Hello!',
include: {
requestBody: true,
responseBody: true,
},
});
```
`ToolLoopAgent` accepts the same `include` setting in its constructor. For `streamText` and `ToolLoopAgent.stream()`, only the request body can be retained; use `include: { requestBody: true }`.
### Runs and steps
DevTools organizes captured data into runs and steps:
- **Run**: A complete multi-step AI interaction, grouped by the initial prompt
- **Step**: A single LLM call within a run (e.g., one `generateText` or `streamText` call)
Multi-step interactions, such as those created by tool calling or agent loops, are grouped together as a single run with multiple steps. Nested sub-agent calls are linked to their parent run, making it easy to trace the full execution tree.
## How it works
The `DevToolsTelemetry` integration hooks into the AI SDK [telemetry](/docs/ai-sdk-core/telemetry) lifecycle to capture all `generateText`, `streamText`, `generateObject`, and `streamObject` calls. Captured data is stored locally in a JSON file (`.devtools/generations.json`) and served through a web UI built with Hono and React.
<Note type="warning">
The integration automatically adds `.devtools` to your `.gitignore` file.
Verify that `.devtools` is in your `.gitignore` to ensure you don't commit
sensitive AI interaction data to your repository.
</Note>
## Security considerations
DevTools stores all AI interactions locally in plain text files, including:
- User prompts and messages
- LLM responses
- Tool call arguments and results
- API request and response data when body retention is enabled
**Only use DevTools in local development environments.** Do not enable DevTools in production or when handling sensitive data.