Connect SmartTask and MongoDB to Build Intelligent Automations
Choose a Trigger
When this happens...
New Contact
New Task
Task Completion
Task Comment Added
Choose an Action
Automatically do this!
- Request a new Action for MongoDB
Enable Integrations or automations with these events of SmartTask and MongoDB
Enable Integrations or automations with these events of SmartTask and MongoDB
Triggers
New Contact
Triggers when a new contact is added to the organization.
New Task
Triggers when a new task is added to the project.
Task Completion
Triggers when a task is marked completed.
Task Comment Added
Triggers when a comment is added on task .
Actions
List Organizations
Retrieve all the list of organizatons
Create Task
Creates a new task
List User
Retrieve the list of users
List Project
Retrieve list of all projects
Add Comment to Task
Adds a new comment to task
Create Contact
Creates a new contact
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Frequently Asked Questions
To start, connect both your SmartTask and MongoDB accounts to viaSocket. Once connected, you can set up a workflow where an event in SmartTask triggers actions in MongoDB (or vice versa).
Absolutely. You can customize how SmartTask data is recorded in MongoDB. This includes choosing which data fields go into which fields of MongoDB, setting up custom formats, and filtering out unwanted information.
The data sync between SmartTask and MongoDB typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between SmartTask and MongoDB. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About SmartTask
SmartTask is an online work management tool helping teams streamline their communication and workflows.
Learn MoreAbout MongoDB
MongoDB is a leading NoSQL database platform that provides a flexible and scalable solution for managing large volumes of data. It is designed to handle unstructured data and offers high performance, high availability, and easy scalability.
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