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Sync MongoDB data to Lark for instant notifications. Latenode’s visual editor simplifies building complex alerts without code, while affordable execution-based pricing makes scaling effortless. Add custom JavaScript logic for advanced data formatting.
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Create a New Scenario to Connect MongoDB and Lark
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 MongoDB, triggered by another scenario, or executed manually (for testing purposes). In most cases, MongoDB or Lark will be your first step. To do this, click "Choose an app," find MongoDB or Lark, and select the appropriate trigger to start the scenario.
Add the MongoDB Node
Select the MongoDB node from the app selection panel on the right.
MongoDB
Add the Lark Node
Next, click the plus (+) icon on the MongoDB node, select Lark from the list of available apps, and choose the action you need from the list of nodes within Lark.
MongoDB
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Lark
Authenticate Lark
Now, click the Lark node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Lark settings. Authentication allows you to use Lark through Latenode.
Configure the MongoDB and Lark 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 MongoDB and Lark Integration
Use various Latenode nodes to transform data and enhance your integration:
JavaScript
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AI Anthropic Claude 3
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Lark
Trigger on Webhook
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MongoDB
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring MongoDB, Lark, 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 MongoDB and Lark integration works as expected. Depending on your setup, data should flow between MongoDB and Lark (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
MongoDB + Jira + Lark: When a new error document is logged in MongoDB, a new issue is created in Jira to track the error. A message is then sent to a Lark group chat to notify the team about the new Jira issue.
Lark + MongoDB + Google Sheets: When a new message is received in a Lark group chat, the message details are saved as a document in MongoDB. Then, a summary of the Lark messages stored in MongoDB is added as a new row in a Google Sheet.
About MongoDB
Use MongoDB in Latenode to automate data storage and retrieval. Aggregate data from multiple sources, then store it in MongoDB for analysis or reporting. Latenode lets you trigger workflows based on MongoDB changes, create real-time dashboards, and build custom integrations. Low-code tools and JavaScript nodes unlock flexibility for complex data tasks.
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About Lark
Use Lark within Latenode to centralize team comms & automate notifications based on workflow triggers. Aggregate messages, streamline approvals, and post updates to specific channels. Benefit from Latenode's visual editor and logic tools for advanced routing that keeps everyone informed and aligned.
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How can I connect my MongoDB account to Lark using Latenode?
To connect your MongoDB account to Lark on Latenode, follow these steps:
Can I send new MongoDB entries to Lark as messages?
Yes, you can! Latenode's visual editor makes it easy to trigger Lark messages from new MongoDB entries, keeping your team informed in real-time about database updates.
What types of tasks can I perform by integrating MongoDB with Lark?
Integrating MongoDB with Lark allows you to perform various tasks, including:
How can I transform MongoDB data before sending to Lark in Latenode?
Latenode lets you transform MongoDB data with JavaScript or AI steps before sending to Lark, ensuring correct formatting and relevant content.
Are there any limitations to the MongoDB and Lark integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: