Feature Marketplace · Connectors
Calendly Connector
Calendly scheduling automation platform. Syncs scheduled events, event types, and invitees via the Calendly API v2 with signed webhooks for real-time booking notifications.
What syncs
The Calendly records STRAX brings into your hub.
Each kind of record is mapped once to your company model in the STRAX hub, then kept current in every system that needs it. Where Calendly announces changes, they arrive as they happen.
Scheduled Events
Meetings booked on the user's calendar, including status, start and end times, and location.
Changes arrive as they happenEvent Types
Bookable meeting templates including duration, kind, pooling type, and scheduling URL.
Invitees
People who booked a scheduled event, including contact details, status, and reschedule links.
Changes arrive as they happenCalendly data in your own SQL Server, then wherever it is needed.
STRAX is a self-hosted integration platform. The Calendly records land in the STRAX hub, a SQL Server database on your own servers, where your reports, portals and workflows read them. From there the hub delivers them to the other systems you connect, whether those run on SQL Server, MySQL, PostgreSQL or another API. STRAX signs in to Calendly with an access token that you provide, stored encrypted.
How STRAX connectors work → How the STRAX integration engine works → Connecting a system, in the documentation →
About this listing
| Version | 1.0.1 |
| Author | STRAX |
| Category | Connectors |
| Published | 2026-07-15 |
What's inside
| Connector profile | 1 |
Free listing
Install it from Feature Marketplace inside STRAX
Open Feature Marketplace
In your STRAX installation, open Feature Marketplace from the navigation.
Find "Calendly Connector"
Search or browse to this listing and review the contents disclosure; every package shows what it contains before anything runs.
Install
Choose Install, or "Customise with AI" to adapt the package to your environment first. No licence is needed for free listings.
See it on your own systems.
A demo takes an hour, on your data landscape rather than ours.