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182 changes: 182 additions & 0 deletions content/en/agentic_onboarding/setup.md
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---
title: Agentic Onboarding Setup
description: Set up the Datadog MCP server to instrument your frontend applications with coding agents like Cursor or Claude Code.
further_reading:

---

{{< callout btn_hidden="true" header="Join the Preview!">}}
Agentic Onboarding is in Preview.
{{< /callout >}}

{{< site-region region="gov" >}}
<div class="alert alert-danger">Agentic Onboarding is not available in the selected site ({{< region-param key="dd_site_name" >}}) at this time.</div>
{{< /site-region >}}

## Overview

Datadog's Agentic Onboarding allows you to instrument your frontend applications with one prompt using LLM coding agents like [Cursor][1] or [Claude Code][2].

Instead of navigating multiple setup steps or searching through documentation, you can instrument your frontend applications for [Error Tracking][3], [Real User Monitoring (RUM)][4], and [Product Analytics][5] in one command.

With Agentic Onboarding, your coding assistant automatically detects your project's frameworks, add configuration, and provisions required tokens and apps directly from your IDE.

## Prerequisites
### Supported frameworks
Agentic Onboarding is available for the following frameworks: Android, Angular, iOS, Next.js, Svelte, Vanilla JS, Vue

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We have support for React - just not React Native.

Apologies for the confusion on this!


## Setup

### Install the Datadog Onboarding MCP server

To install the Datadog Onboarding Model Context Protocol (MCP) server, follow the steps below.

{{< tabs >}}
{{% tab "Cursor" %}}
1. Copy and paste the following deeplink into your browser.

{{% site-region region="us" %}}

```shell
cursor://anysphere.cursor-deeplink/mcp/install?name=datadog-onboarding-mcp&config=eyJ1cmwiOiJodHRwczovL21jcC5kYXRhZG9naHEuY29tL2FwaS91bnN0YWJsZS9tY3Atc2VydmVyL21jcD90b29sc2V0cz1vbmJvYXJkaW5nIiwidHlwZSI6Im9hdXRoIn0=
```
{{% /site-region %}}

{{% site-region region="us3" %}}
```shell
cursor://anysphere.cursor-deeplink/mcp/install?name=datadog-onboarding-us3&config=eyJ1cmwiOiJodHRwczovL21jcC51czMuZGF0YWRvZ2hxLmNvbS9hcGkvdW5zdGFibGUvbWNwLXNlcnZlci9tY3A/dG9vbHNldHM9b25ib2FyZGluZyIsInR5cGUiOiJvYXV0aCJ9
```
{{% /site-region %}}

{{% site-region region="us5" %}}
```shell
cursor://anysphere.cursor-deeplink/mcp/install?name=datadog-onboarding-us5&config=eyJ1cmwiOiJodHRwczovL21jcC51czUuZGF0YWRvZ2hxLmNvbS9hcGkvdW5zdGFibGUvbWNwLXNlcnZlci9tY3A/dG9vbHNldHM9b25ib2FyZGluZyIsInR5cGUiOiJvYXV0aCJ9
```
{{% /site-region %}}

{{% site-region region="eu" %}}
```shell
cursor://anysphere.cursor-deeplink/mcp/install?name=datadog-onboarding-mcp&config=eyJ1cmwiOiJodHRwczovL21jcC5kYXRhZG9naHEuZXUvYXBpL3Vuc3RhYmxlL21jcC1zZXJ2ZXIvbWNwP3Rvb2xzZXRzPW9uYm9hcmRpbmciLCJ0eXBlIjoib2F1dGgifQ==
```
{{% /site-region %}}

{{% site-region region="ap1" %}}
```shell
cursor://anysphere.cursor-deeplink/mcp/install?name=datadog-onboarding-ap1&config=eyJ1cmwiOiJodHRwczovL21jcC5hcDEuZGF0YWRvZ2hxLmNvbS9hcGkvdW5zdGFibGUvbWNwLXNlcnZlci9tY3A/dG9vbHNldHM9b25ib2FyZGluZyIsInR5cGUiOiJvYXV0aCJ9
```
{{% /site-region %}}

{{% site-region region="ap2" %}}
```shell
cursor://anysphere.cursor-deeplink/mcp/install?name=datadog-onboarding-ap2&config=eyJ1cmwiOiJodHRwczovL21jcC5hcDIuZGF0YWRvZ2hxLmNvbS9hcGkvdW5zdGFibGUvbWNwLXNlcnZlci9tY3A/dG9vbHNldHM9b25ib2FyZGluZyIsInR5cGUiOiJvYXV0aCJ9
```
{{% /site-region %}}

{{< site-region region="gov" >}}
<div class="alert alert-danger">Agentic Onboarding is not available in the selected site ({{< region-param key="dd_site_name" >}}) at this time.</div>
{{< /site-region >}}

2. In Cursor, click **Install** for the `datadog-onboarding-mcp` server.
3. If the MCP server shows a **Needs login** link, select it and complete the OAuth flow. When prompted, choose **Open** to continue and grant access to your Datadog account.
4. After authentication, return to Cursor and confirm that MCP tools appear under the `datadog-onboarding-mcp` server.

{{% /tab %}}

{{% tab "Claude Code" %}}

1. Open an active Claude Code session with the /mcp command:

{{% site-region region="us" %}}
```shell
claude mcp add --transport http datadog-onboarding-us1 "https://mcp.datadoghq.com/api/unstable/mcp-server/mcp?toolsets=onboarding"
```
{{% /site-region %}}

{{% site-region region="us3" %}}
```shell
claude mcp add --transport http datadog-onboarding-us3 "https://mcp.us3.datadoghq.com/api/unstable/mcp-server/mcp?toolsets=onboarding"
```
{{% /site-region %}}

{{% site-region region="us5" %}}
```shell
claude mcp add --transport http datadog-onboarding-us5 "https://mcp.us5.datadoghq.com/api/unstable/mcp-server/mcp?toolsets=onboarding"
```
{{% /site-region %}}

{{% site-region region="eu" %}}
```shell
claude mcp add --transport http datadog-onboarding-eu1 "https://mcp.datadoghq.eu/api/unstable/mcp-server/mcp?toolsets=onboarding
```
{{% /site-region %}}
{{% site-region region="ap1" %}}
```shell
claude mcp add --transport http datadog-onboarding-ap1 "https://mcp.ap1.datadoghq.com/api/unstable/mcp-server/mcp?toolsets=onboarding"
```
{{% /site-region %}}
{{% site-region region="ap2" %}}
```shell
claude mcp add --transport http datadog-onboarding-ap2 "https://mcp.ap2.datadoghq.com/api/unstable/mcp-server/mcp?toolsets=onboarding"
```
{{% /site-region %}}
{{< site-region region="gov" >}}
<div class="alert alert-danger">Agentic Onboarding is not available in the selected site ({{< region-param key="dd_site_name" >}}) at this time.</div>
{{< /site-region >}}
2. Select the MCP server installed in Step 1. You should see a `disconnected - Enter to login` message. Press <kbd>Enter</kbd>.
3. When you see the option to authenticate, press <kbd>Enter</kbd>. This brings you to the OAuth screen.
{{% /tab %}}
{{< /tabs >}}
### Set up your project
Your AI coding agent can help configure Datadog for your project. When you provide a setup prompt, it:
- analyzes your project and identifies your project's framework, language, and bundler
- calls the tool, asking for your permission before it runs
**Note**: Your coding agent makes changes locally without committing them.
- applies the configuration changes specified by the tool
- provides steps to verify that your application is sending telemetry to Datadog
1. To get started, copy and paste the following prompt based on the product you want to use into your coding agent (such as Cursor or Claude Code):
{{< tabs >}}
{{% tab "Error Tracking" %}}
```console
Add Datadog Error Tracking to my project
```
{{% /tab %}}
{{% tab "Real User Monitoring" %}}
```console
Add Datadog Real User Monitoring to my project
```
{{% /tab %}}
{{% tab "Product Analytics" %}}
```console
Add Datadog Product Analytics to my project
```
{{% /tab %}}
{{< /tabs >}}
2. After pasting the prompt, review and accept each action your AI agent proposes to move through the setup process.
### Deploy your app to production
Commmit the changes in your repository and configure the provided environment variables in your production environment.
[1]: https://cursor.com/
[2]: https://claude.ai/
[3]: /error_tracking/frontend/
[4]: /real_user_monitoring/
[5]: /product_analytics/
[6]: https://platform.openai.com/docs/guides/text
[7]: https://github.com/langchain-ai/langgraph
[8]: https://github.com/vercel/ai-chatbot
13 changes: 13 additions & 0 deletions content/en/error_tracking/_index.md
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Expand Up @@ -23,6 +23,19 @@ Additional features are available depending on the source of the error. See [sup
- Take a tour of key Error Tracking features in the [Error Tracking Explorer][5] documentation.
- Use the product-specific links in the next section to set up Error Tracking for a particular error source.

## Setup
{{< whatsnext desc="To get started with Datadog Error Tracking, see the corresponding documentation:" >}}
{{< nextlink href="agentic_onboarding/setup" >}}Agentic Onboarding{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/browser" >}}Browser{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/mobile/android" >}}Android{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/mobile/ios" >}}iOS{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/mobile/expo" >}}Expo{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/mobile/reactnative" >}}React Native{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/mobile/flutter" >}}Flutter{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/mobile/kotlin_multiplatform" >}}Kotlin Multiplatform{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/logs" >}}Logs{{< /nextlink >}}
{{< /whatsnext >}}

## Supported error sources

Error Tracking captures and processes errors across your web, mobile, and backend applications. You can instrument your applications and services using the [Browser SDK][6], [Mobile SDK][7], or ingest errors from your Logs, Traces, and Real User Monitoring events.
Expand Down
5 changes: 3 additions & 2 deletions content/en/error_tracking/frontend/_index.md
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Expand Up @@ -25,13 +25,14 @@ It is critical for your system’s health to consistently monitor the errors col
Error Tracking simplifies debugging by grouping thousands of similar errors into a single issue. Error Tracking enables you to:

- Track, triage, and debug fatal errors
- Group similar errors into issues, so that you can more easily identify important errors and reduce noise
- Group similar errors into issues to identify important errors and reduce noise
- Set monitors on error tracking events, such as high error volume or new issues
- Follow issues over time to know when they first started, if they are still ongoing, and how often they occur
- See a detailed timeline of steps a user took leading up to the error, simplifying the process to reproduce and resolve errors quickly
- See a detailed timeline of steps a user took leading up to the error, simplifying the process to reproduce and resolve errors

## Setup
{{< whatsnext desc="To get started with Datadog Error Tracking, see the corresponding documentation:" >}}
{{< nextlink href="agentic_onboarding/setup" >}}Agentic Onboarding (frontend only){{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/browser" >}}Browser{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/mobile/android" >}}Android{{< /nextlink >}}
{{< nextlink href="error_tracking/frontend/mobile/ios" >}}iOS{{< /nextlink >}}
Expand Down
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---
title: Agentic Onboarding for RUM
description: Instrument your frontend application with one prompt using LLM coding agents like Cursor or Claude.
---

{{< include-markdown "agentic_onboarding/setup" >}}
Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,14 @@ The Datadog Android SDK supports Android 6.0+ (API level 23) and Android TV.

## Setup

To start sending RUM data from your Android or Android TV application to Datadog:
**Choose your setup method:**

- **[Agentic Onboarding (in Preview)][18]**: Use AI coding agents (Cursor, Claude Code) to automatically instrument your Android application with one prompt. The agent detects your project structure and configures the RUM SDK for you.
- **Manual setup** (below): Follow the step-by-step instructions to manually add and configure the RUM SDK in your Android application.

### Manual setup

To start sending RUM data from your Android or Android TV application to Datadog, follow the steps below.

### Step 1 - Declare the Android SDK as a dependency

Expand Down Expand Up @@ -637,3 +644,4 @@ val inputStream = context.getRawResAsRumResource(id)
[15]: https://square.github.io/okhttp/features/interceptors/#network-interceptors
[16]: /real_user_monitoring/application_monitoring/android/advanced_configuration/#automatically-track-network-requests
[17]: https://square.github.io/okhttp/features/interceptors/
[18]: /real_user_monitoring/application_monitoring/agentic_onboarding/?tab=realusermonitoring
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Expand Up @@ -12,22 +12,25 @@ further_reading:
## Setup

{{< whatsnext desc="Choose the instrumentation type for the Browser SDK:" >}}
{{< nextlink href="real_user_monitoring/application_monitoring/browser/setup/client">}}<u>Client-Side</u>: Instrument each of your browser-based web applications, deploy the application, then configure the initialization parameters you want to track, and use advanced configuration to further manage data and context that RUM collects.{{< /nextlink >}}
{{< nextlink href="/real_user_monitoring/application_monitoring/browser/setup/server">}}<u>Auto-Instrumentation</u>: Inject a RUM SDK JavaScript scriptlet into the HTML responses of your web applications being served through a web server or proxy.{{< /nextlink >}}
{{< nextlink href="/real_user_monitoring/application_monitoring/agentic_onboarding">}}<u>Agentic Onboarding</u>: Instrument your frontend applications with one prompt using LLM coding agents like Cursor or Claude.{{< /nextlink >}}
{{< nextlink href="real_user_monitoring/application_monitoring/browser/setup/client">}}<u>Client-Side</u>: Instrument each of your browser-based web applications, deploy the application, then configure the initialization parameters you want to track, and use advanced configuration to further manage data and context that RUM collects.{{< /nextlink >}}
{{< /whatsnext >}}

## How to choose the instrumentation type

| | Auto-instrumentation (Preview) | Client-side (Manual) |
|----------------------|--------------------------------|----------------------|
| **SDK setup mechanism** | [Automatically][1] add RUM JS to your web app HTML. Once RUM Auto-instrumentation is set-up, manage configurations from the UI. | [Manually][2] add the RUM SDK to your application code and manage configurations in code. |
| **Code changes required** | No | Yes |
| **Setup complexity** | Low | Medium |
| **User groups** | **SRE and engineering teams** without access to frontend code, or **teams who need to manage** all observability needs centrally, may find this useful for: <br> - Unlocking performance data across all applications upon setting up RUM <br> - Holistically monitoring application performance across the organization | **Frontend engineering, mobile engineering, or product teams** with access to frontend code may find this method useful for: <br> - Daily engineering needs (for example: live support, troubleshooting, and health checks for downstream services) <br> -Product needs (for example: user flow analysis, user segmentation, and feature flag tracking) <br> - Capturing observability from in-house code or complex functions that aren't captured by automatic instrumentation |
| | Auto-instrumentation (Preview) | Agentic Onboarding (Preview) | Client-side (Manual) |
|----------------------|--------------------------------|------------------------------|----------------------|
| **SDK setup mechanism** | [Automatically][1] add RUM JS to your web app HTML. Once RUM Auto-instrumentation is set-up, manage configurations from the UI. | [AI-guided setup][3] that automatically detects your project's framework and adds the RUM SDK with one prompt using coding agents. | [Manually][2] add the RUM SDK to your application code and manage configurations in code. |
| **Code changes required** | No | Yes (automated by AI agent) | Yes |
| **Setup complexity** | Low | Low | Medium |
| **Supported platforms** | Apache, IBM HTTP Server, Java Servlet, Nginx, Windows IIS | Next.js, React, Svelte, Vue, Vanilla JavaScript | All browser-based applications |
| **User groups** | **SRE and engineering teams** without access to frontend code, or **teams who need to manage** all observability needs centrally, may find this useful for: <br> - Unlocking performance data across all applications upon setting up RUM <br> - Holistically monitoring application performance across the organization | **Teams using AI coding agents** (Cursor, Claude Code) may find this useful for: <br> - Accelerating RUM setup with AI-guided instrumentation <br> - Automating framework detection and SDK configuration <br> - Reducing time-to-observability for new projects | **Frontend engineering, mobile engineering, or product teams** with access to frontend code may find this method useful for: <br> - Daily engineering needs (for example: live support, troubleshooting, and health checks for downstream services) <br> -Product needs (for example: user flow analysis, user segmentation, and feature flag tracking) <br> - Capturing observability from in-house code or complex functions that aren't captured by automatic instrumentation |

## Further reading

{{< partial name="whats-next/whats-next.html" >}}

[1]: /real_user_monitoring/application_monitoring/browser/setup/server
[2]: /real_user_monitoring/application_monitoring/browser/setup/client
[3]: /real_user_monitoring/application_monitoring/agentic_onboarding/?tab=realusermonitoring
Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,14 @@ Before you begin, ensure you have:

## Setup

To start sending RUM data from your iOS or tvOS application to Datadog:
**Choose your setup method:**

- **[Agentic Onboarding (in Preview)][14]**: Use AI coding agents (Cursor, Claude Code) to automatically instrument your iOS application with one prompt. The agent detects your project structure and configures the RUM SDK for you.
- **Manual setup** (below): Follow the step-by-step instructions to manually add and configure the RUM SDK in your iOS application.

### Manual setup

To start sending RUM data from your iOS or tvOS application to Datadog, follow the steps below.

### Step 1 - Add the iOS SDK as a dependency

Expand Down Expand Up @@ -553,3 +560,4 @@ See [Supported versions][9] for a list of operating system versions and platform
[11]: /real_user_monitoring/ios/web_view_tracking/
[12]: /real_user_monitoring/ios/data_collected/
[13]: https://app.datadoghq.com/rum/application/
[14]: /real_user_monitoring/application_monitoring/agentic_onboarding/?tab=realusermonitoring
Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,15 @@ The React Native SDK supports the following services:

## Setup

**Choose your setup method:**

- **[Agentic Onboarding (in Preview)][15]**: Use AI coding agents (Cursor, Claude Code) to automatically instrument your React Native application with one prompt. The agent detects your project structure and configures the RUM SDK for you.
- **Manual setup** (below): Follow the step-by-step instructions to manually add and configure the RUM SDK in your React Native application.

### Manual setup

To start sending RUM data from your React Native application to Datadog, follow the steps below.

To install with NPM, run:

```sh
Expand Down Expand Up @@ -478,3 +487,4 @@ end
[12]: https://support.apple.com/guide/security/security-of-runtime-process-sec15bfe098e/web
[13]: https://stackoverflow.com/questions/37388126/use-frameworks-for-only-some-pods-or-swift-pods/60914505#60914505
[14]: https://reactnative.dev/architecture/landing-page
[15]: /real_user_monitoring/application_monitoring/ios/agentic_onboarding/?tab=realusermonitoring
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