How to connect Microsoft SQL Server and OpenAI Responses
Create a New Scenario to Connect Microsoft SQL Server and OpenAI Responses
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Microsoft SQL Server, triggered by another scenario, or executed manually (for testing purposes). In most cases, Microsoft SQL Server or OpenAI Responses will be your first step. To do this, click "Choose an app," find Microsoft SQL Server or OpenAI Responses, and select the appropriate trigger to start the scenario.

Add the Microsoft SQL Server Node
Select the Microsoft SQL Server node from the app selection panel on the right.


Microsoft SQL Server

Configure the Microsoft SQL Server
Click on the Microsoft SQL Server node to configure it. You can modify the Microsoft SQL Server URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the OpenAI Responses Node
Next, click the plus (+) icon on the Microsoft SQL Server node, select OpenAI Responses from the list of available apps, and choose the action you need from the list of nodes within OpenAI Responses.


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Authenticate OpenAI Responses
Now, click the OpenAI Responses node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your OpenAI Responses settings. Authentication allows you to use OpenAI Responses through Latenode.
Configure the Microsoft SQL Server and OpenAI Responses Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Microsoft SQL Server and OpenAI Responses Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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AI Anthropic Claude 3
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OpenAI Responses
Trigger on Webhook
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Save and Activate the Scenario
After configuring Microsoft SQL Server, OpenAI Responses, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Microsoft SQL Server and OpenAI Responses integration works as expected. Depending on your setup, data should flow between Microsoft SQL Server and OpenAI Responses (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Microsoft SQL Server and OpenAI Responses
Microsoft SQL Server + OpenAI Responses + Slack: When a new or updated row is detected in Microsoft SQL Server based on a custom query, the data is sent to OpenAI to generate key insights. These insights are then posted to a dedicated Slack channel to keep the team informed.
Google Sheets + OpenAI Responses + Microsoft SQL Server: When a new row is added to a Google Sheet, it's sent to OpenAI Responses for summarization. The generated summary is then stored in a Microsoft SQL Server database for record-keeping.
Microsoft SQL Server and OpenAI Responses integration alternatives

About Microsoft SQL Server
Use Microsoft SQL Server in Latenode to automate database tasks. Directly query, update, or insert data in response to triggers. Sync SQL data with other apps; simplify data pipelines for reporting and analytics. Build automated workflows without complex coding to manage databases efficiently and scale operations.
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About OpenAI Responses
Need AI-powered text generation? Use OpenAI Responses in Latenode to automate content creation, sentiment analysis, and data enrichment directly within your workflows. Streamline tasks like generating product descriptions or classifying customer feedback. Latenode lets you chain AI tasks with other services, adding logic and routing based on results – all without code.
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See how Latenode works
FAQ Microsoft SQL Server and OpenAI Responses
How can I connect my Microsoft SQL Server account to OpenAI Responses using Latenode?
To connect your Microsoft SQL Server account to OpenAI Responses on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Microsoft SQL Server and click on "Connect".
- Authenticate your Microsoft SQL Server and OpenAI Responses accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically enrich database records with AI-generated summaries?
Yes, you can! Latenode's visual editor makes it simple to trigger OpenAI Responses from SQL updates, enriching your data with AI for enhanced analysis and insights.
What types of tasks can I perform by integrating Microsoft SQL Server with OpenAI Responses?
Integrating Microsoft SQL Server with OpenAI Responses allows you to perform various tasks, including:
- Generate personalized email responses based on customer data.
- Analyze customer feedback stored in SQL and identify key trends.
- Create AI-driven reports from your SQL Server data.
- Translate database content into multiple languages automatically.
- Use AI to categorize and tag new entries in your database.
How does Latenode handle Microsoft SQL Server data security?
Latenode provides secure data handling using encrypted connections and follows best practices to ensure your Microsoft SQL Server data is protected during integration.
Are there any limitations to the Microsoft SQL Server and OpenAI Responses integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large datasets may require optimized queries for efficient processing.
- Complex SQL queries might require JavaScript code for customization.
- Rate limits of OpenAI Responses API apply to the integration.