How to connect Google Meet and Monster API
Create a New Scenario to Connect Google Meet and Monster API
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 Google Meet, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Meet or Monster API will be your first step. To do this, click "Choose an app," find Google Meet or Monster API, and select the appropriate trigger to start the scenario.

Add the Google Meet Node
Select the Google Meet node from the app selection panel on the right.

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

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Monster API

Authenticate Monster API
Now, click the Monster API node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Monster API settings. Authentication allows you to use Monster API through Latenode.
Configure the Google Meet and Monster API 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 Google Meet and Monster API 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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Monster API
Trigger on Webhook
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Google Meet
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Iterator
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Webhook response

Save and Activate the Scenario
After configuring Google Meet, Monster API, 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 Google Meet and Monster API integration works as expected. Depending on your setup, data should flow between Google Meet and Monster API (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Meet and Monster API
Google Meet + Monster API + Slack: This automation listens for new messages posted to a specific Slack channel. It then uses the Monster API to analyze the text of the message and identify key skills mentioned. Finally, it posts the identified skills back to the same Slack channel.
Monster API + Google Meet + Email: When a new job application contains skills that match the job description (using Monster API to perform the matching), schedule an interview in Google Meet and send a confirmation email to the candidate.
Google Meet and Monster API integration alternatives
About Google Meet
Automate Google Meet within Latenode workflows. Schedule meetings based on triggers, automatically generate invites after form submissions, or record & transcribe calls, saving time and ensuring consistent follow-up. Connect Meet to CRMs or project tools for streamlined task management. Simplify repetitive scheduling and meeting-related tasks.
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About Monster API
Struggling with unreliable or slow data? Integrate Monster API in Latenode to build automated data validation and cleansing workflows. Use its data enrichment and verification features to refine your data, then route the cleaned info to other services. Benefit from Latenode's visual editor and scalability for consistent, error-free data flow.
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See how Latenode works
FAQ Google Meet and Monster API
How can I connect my Google Meet account to Monster API using Latenode?
To connect your Google Meet account to Monster API on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Meet and click on "Connect".
- Authenticate your Google Meet and Monster API accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze meeting transcript sentiment via Monster API?
Yes, you can analyze Google Meet transcript sentiment using Monster API on Latenode. Latenode’s AI blocks and JavaScript steps enable advanced text processing, extending the basic integration for deeper insights.
What types of tasks can I perform by integrating Google Meet with Monster API?
Integrating Google Meet with Monster API allows you to perform various tasks, including:
- Automatically transcribe Google Meet recordings using Monster API.
- Analyze meeting transcripts for key topics and sentiment.
- Extract action items from meeting transcripts using AI.
- Summarize meeting content with Monster API's text summarization.
- Route transcript data to other apps via Latenode's logic blocks.
How secure is my Google Meet data when using Latenode?
Latenode employs robust security measures, including encryption and access controls, ensuring your Google Meet data is securely processed and stored within your workflows.
Are there any limitations to the Google Meet and Monster API integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Real-time transcription support may depend on Monster API's capabilities.
- Large video file processing might consume significant Latenode resources.
- Complex sentiment analysis requires careful prompt engineering.