Google Contacts
Import your Google Contacts as canonical `person` nodes in the workspace knowledge graph. Establishes the people corpus your other connectors dedupe against.
Google Contacts
Seed the canonical `person` corpus the other connectors dedupe against.
The Contacts connector pulls every contact in your Google account (including "Other contacts" — people you've emailed or who have emailed you, even if you haven't explicitly added them) and writes them as canonical person nodes in your workspace.
Connecting Contacts first is often the right move: it seeds the people corpus that Gmail, Calendar, Meet, and Zoom dedupe against. A person node created by Contacts is the same node your other connectors find on subsequent syncs — they add edges rather than minting duplicates.
What gets ingested
| Source | Node type | Properties |
|---|---|---|
| Contact (incl. "other contacts") | person | email, display_name, optional phone, organization, title, notes |
The connector runs in full sync mode (not incremental) — every sync re-pulls the entire contact list and converges via the find-or-create resolver. Default cadence is 1 hour.
Real use cases
- Seed the people corpus — connecting Contacts before Gmail / Calendar / Zoom means every person ingested elsewhere finds an existing match instead of creating a new node.
- Org-aware action items — Contacts populates the
organizationproperty onpersonnodes, so action items assigned to a person carry the company context automatically. - Phone-number bridge — phone-only meeting attendees from Meet or Zoom can later be backfill-matched to Contacts entries with the same number.
Settings
This connector has no user-configurable settings — it's a directory sync, and there's nothing to tune.
OAuth scopes
contacts.readonly— read the user's own contact listcontacts.other.readonly— read the "Other contacts" list (people emailed but not explicitly added)userinfo.email— resolve the connecting user's email
Zoom Meetings
Ingest Zoom meetings, attendees, and recorded transcripts into the workspace knowledge graph. The connector infers action items, deliverables, decisions, problems, and opportunities as typed nodes and wires them to the people they belong to.
Google Drive
Ingest Google Docs, Sheets, Slides, and PDFs into the workspace knowledge graph. File metadata and extracted text feed the LLM extractor so the topics, people, and concepts in your documents become typed nodes.