Agentic Onboarding for Product Analytics

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Agentic Onboarding is in Preview.

Overview

Agentic Onboarding lets LLM coding agents instrument your frontend applications for Error Tracking, Real User Monitoring (RUM), Product Analytics, and Infrastructure Monitoring with a single prompt.

Your coding assistant, such as Cursor or Claude Code, detects your project’s frameworks, adds configuration, and provisions required tokens and apps directly from your IDE.

Supported frameworks

Agentic Onboarding is available for the following frameworks:

  • Error Tracking, RUM, and Product Analytics: Android, Angular, iOS, Next.js, React, Svelte, Vanilla JS, and Vue.
  • Infrastructure Monitoring with Kubernetes: Terraform, Ansible, Kustomize, and more.

Setup

Install the Datadog Onboarding MCP server

To install the Datadog Onboarding Model Context Protocol (MCP) server, follow the steps for your coding assistant:

    Agentic Onboarding is not available in the selected site ().

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

      claude mcp add --transport http datadog-onboarding- "https://mcp./api/unstable/mcp-server/mcp?toolsets=onboarding"

    2. Select the MCP server installed in Step 1. You should see a disconnected - Enter to login message. Press Enter.

    3. When you see the option to authenticate, press Enter. This brings you to the OAuth screen.

    4. After authentication, choose Open to continue and grant access to your Datadog account.

    5. Confirm that MCP tools appear under the datadog-onboarding- server.

    Agentic Onboarding is not available in the selected site ().

    1. Copy and paste the following deeplink into your browser:

    2. In Cursor, click Install for the datadog-onboarding- server.

    3. If the MCP server shows a Needs login or Connect 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- server.

    Set up your project

    Your AI coding agent can help configure Datadog for your project. When you provide a setup prompt, the agent:

    • Analyzes your project and identifies the framework, language, and bundler
    • Calls the MCP tool and requests permission before running
    • Applies the configuration changes specified by the tool
    • Provides steps to verify that your application is sending telemetry to Datadog

    Note: Your coding agent makes changes locally but does not commit them.

    To get started:

    1. Choose the product you want to use and paste its setup prompt into your AI agent:

        Add Datadog Error Tracking to my project

        Add Datadog Real User Monitoring to my project

        Add Datadog Product Analytics to my project

        Add Datadog for Kubernetes to my project

      • Review and accept each action your AI agent proposes to complete the setup process.

      Deploy your app to production

      Commit the changes to your repository and configure the provided environment variables in your production environment.