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Google Calendar is Google’s time management and scheduling application that helps users organize events, meetings, and appointments. It provides features for calendar sharing, event reminders, and integration with other Google services for seamless scheduling and time management.

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Configuring Google Calendar as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Google Calendar option from the list of connectors. Click Next and you’ll be prompted to add your access.

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1. Add account access

You’ll need to authorize Nekt to access your Google Calendar data. Click on the Google Authorization button and log in with your Google account. The following configurations are available:
  • Start Date: The earliest date from which event records will be synced.
  • Calendar IDs Filter: (Optional) A list of specific calendar IDs to extract. If empty, all calendars available to the authenticated account are included.
Once you’re done, click Next.

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2. Select streams

Choose which data streams you want to sync. Google Calendar streams are generated dynamically, one per calendar, with names following the pattern events_<calendar_name_slug>.
Tip: The stream can be found more easily by typing its name.
Select the streams and click Next.

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3. Configure data streams

Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table (which will effectively contain the fetched data), and the type of sync.
  • Layer: choose between the existing layers on your catalog. This is where you will find your new extracted tables as the extraction runs successfully.
  • Folder: a folder can be created inside the selected layer to group all tables being created from this new data source.
  • Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix to all tables at once and make this process faster.
  • Sync Type: you can choose between INCREMENTAL and FULL_TABLE.
    • Incremental: every time the extraction happens, we’ll get only the new data, which is useful when you want to keep historical records.
    • Full table: every time the extraction happens, we’ll get the current state of the data, which is useful when you do not want deleted records in your catalog.
Once you are done configuring, click Next.

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4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how frequency you want data to be extracted from this source. This decision usually depends on how frequently you need the new table data updated (every day, once a week, or only at specific times). Optionally, you can define some additional settings:
  • Configure Delta Log Retention and determine for how long we should store old states of this table as it gets updated. Read more about this resource here.
  • Determine when to execute an Additional Full Sync. This will complement the incremental data extractions, ensuring that your data is completely synchronized with your source every once in a while.
Once you are ready, click Next to finalize the setup.

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5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the source extraction by clicking on the arrow button. Once executed, your data will appear in your Catalog.
For you to be able to see it on your Catalog, you need at least one successful source run.

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Streams and Fields

Below you’ll find the available data streams from Google Calendar and their corresponding fields:
Stream for retrieving details about the calendars available to the authenticated user.
Stream for retrieving calendar events from each accessible Google Calendar.Stream naming:
  • events_<calendar_name_slug> - One stream is created per calendar (for example, events_marketing_team)
Selection behavior:
  • If calendar_ids_filter is empty, streams are created for all calendars the authenticated user can access
  • If calendar_ids_filter is provided, only matching calendar IDs are used
Sync behavior:
  • Primary key: id
  • Replication key: updated (incremental sync supported)
  • Deleted events are included in extraction (showDeleted=true)
Key Fields:

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Implementation Notes

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Data behavior considerations

  • Stream names are dynamic and depend on calendar names. Renaming a calendar can change the discovered stream name.
  • The connector uses Google Calendar list data internally to discover calendars before creating event streams.
  • Event payloads can vary by event type (single event, recurring instance, working location), so nested fields may be sparse depending on your account usage.

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Incremental sync limitations & fallbacks

  • Automatic Full Sync for Holiday Calendars: Google’s Holiday calendars (e.g., calendars ending in #holiday@group.v.calendar.google.com) are read-only and load events in bulk with a single updated timestamp. Because their bookmark quickly falls outside of Google’s incremental sync window limit (updatedMin), incremental sync is not meaningful for them. The connector automatically identifies these calendars and will always perform a full sync, overriding the incremental configuration.
  • Expired Incremental Window (updatedMinTooLongAgo): The Google Calendar API enforces a limit on how far in the past an incremental sync request (updatedMin) can be made. If a calendar hasn’t been synced in a long time and the API returns a 410 Gone error with the reason updatedMinTooLongAgo, the connector will seamlessly detect this rejection and automatically fall back to a full sync for that particular run. This built-in resiliency prevents pipeline failures and guarantees your catalog’s data integrity.

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API limits & performance

  • If your account has many calendars, selecting all streams can increase extraction times.
  • Use calendar_ids_filter to reduce the number of discovered streams and improve run performance.

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Skills for agents

Download Google Calendar skills file

Google Calendar connector documentation as plain markdown, for use in AI agent contexts.