HighLevel (GoHighLevel) is a business management platform for service-based businesses. It provides customer relationship management, marketing automation, and operations tooling to help teams capture leads, manage pipelines, and run campaigns.

The connector is built for agency accounts: you authenticate with OAuth, then sync one or more location IDs (sub-accounts) in a single source. All location-scoped streams include location_id so you can filter or join across sub-accounts in the catalog.

Configuring HighLevel as a Source

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

1. Add account access

Authorize Nekt with OAuth using an agency user that can access the locations you want to sync. The following configurations are available:

OAuth (refresh token): Sign in and grant access so Nekt can call the HighLevel API on your behalf.
Location IDs: The sub-account location IDs to include in the sync. See HighLevel help for how to find a location ID.
Start date: Earliest point in time for incremental streams (contacts, opportunities). Records updated on or after this window are considered for historical loads and incremental bookmarks.

Once you’re done, click Next.

2. Select streams

Choose which data streams you want to sync. For faster extractions, select only the streams that are relevant to your analysis. You can select entire groups of streams or pick specific ones.

Tip: The stream can be found more easily by typing its name.

Select the streams and click Next.

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 (contacts, opportunities, notes, tasks): each run fetches updates since the last successful bookmark (driven by API update timestamps and your Start date). Child streams (notes, tasks) automatically merge new or updated records based on their parent contacts.
- Full table (locations, custom_fields, campaigns, pipelines): each run replaces the current snapshot for that table.

Once you are done configuring, click Next.

4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how often 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.

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.

Streams and Fields

Below you’ll find all available data streams from HighLevel and their corresponding fields:

Locations

Reference stream that emits one row per configured Location ID, with the agency company identifier. Child streams (contacts, opportunities, etc.) run in the context of each location.Replication: FULL_TABLE (not incremental). In the tap catalog this stream is off by default; enable it if you want an explicit dimension table of configured locations.

Field	Type	Description
`location_id`	String	Sub-account location identifier
`company_id`	String	Agency company identifier associated with the OAuth token

Contacts

Contacts for each location, loaded via the search API. Incremental replication uses date_updated.

Field	Type	Description
`id`	String	Contact identifier (primary key)
`location_id`	String	Location scope
`first_name`, `last_name`, `first_name_lower_case`, `last_name_lower_case`	String	Contact name profile attributes
`email`, `valid_email`, `phone`, `phone_label`	String	Contact info
`company_name`, `business_name`, `business_id`, `website`	String	Business profile attributes
`address`, `city`, `state`, `country`, `postal_code`	String	Address profile attributes
`date_of_birth`	Integer	Unix timestamp from the API
`type`, `source`, `assigned_to`, `followers`, `tags`, `dnd`	String / Array	Other profile attributes
`additional_emails`	Array	Array of objects (`email`, `valid_email_date`)
`additional_phones`	Array	Array of objects (`phone`, `phone_label`)
`custom_fields`	Array	Array of objects (`id`, `value`). Non-string values are coerced to string/JSON.
`opportunities`	String	JSON string of opportunity payloads returned on the contact
`date_added`, `date_updated`	String	Timestamps (`date_updated` is the replication key)

Notes

Notes attached to contacts, with their text content.One API call per contact, so this stream is off by default in the catalog; enable it when note text is needed in the warehouse.Replication: INCREMENTAL (merges on primary key using date_added).

Field	Type	Description
`id`	String	Note identifier (primary key)
`contact_id`	String	Related contact identifier
`date_added`	String	Creation timestamp (used as replication key to ensure the loader merges records)

Tasks

Tasks attached to contacts, with their text content.One API call per contact, so this stream is off by default in the catalog; enable it when task text is needed in the warehouse.Replication: INCREMENTAL (merges on primary key using due_date).

Field	Type	Description
`id`	String	Task identifier (primary key)
`contact_id`	String	Related contact identifier
`due_date`	String	Deadline timestamp (used as replication key to ensure the loader merges records)

Custom fields

Custom field definitions for the location (for example fields attached to contacts or opportunities).Replication: FULL_TABLE.

Field	Type	Description
`id`	String	Field definition identifier
`location_id`	String	Location scope
`name`, `field_key`, `model`, `data_type`, `placeholder`, `position`	String / Integer	Field metadata
`document_type`, `parent_id`, `standard`	String / Boolean	Field structure attributes
`picklist_options`	Array	Allowed labels (normalized from API options)
`date_added`	String	Timestamp

Campaigns

Marketing campaigns for the location.Replication: FULL_TABLE.

Field	Type	Description
`id`	String	Campaign identifier
`name`	String	Campaign name
`status`	String	Campaign status from the API
`location_id`	String	Location scope

Pipelines

Opportunity pipelines and their stages for the location.Replication: FULL_TABLE.

Field	Type	Description
`id`	String	Pipeline identifier
`name`	String	Pipeline name
`location_id`	String	Location scope
`show_in_funnel`, `show_in_pie_chart`	Boolean	UI flags
`origin_id`	String	Origin identifier
`date_added`, `date_updated`	String	Timestamps
`stages`	Array	Nested array of stages (`id`, `name`, `position`, `show_in_pie_chart`, `show_in_funnel`, `origin_id`)

Opportunities

Opportunities (deals) per location from the search API. Incremental replication uses updated_at (filtered via API date_updated).

Field	Type	Description
`id`	String	Opportunity identifier
`location_id`	String	Location scope
`contact_id`	String	Related contact
`pipeline_id`, `pipeline_stage_id`, `pipeline_stage_u_id`	String	Pipeline associations
`name`, `status`, `source`, `assigned_to`, `followers`	String / Array	Core attributes
`monetary_value`	String	Monetary value (cast explicitly in SQL for numeric aggregations)
`lost_reason_id`, `index_version`	String	Loss tracking and versioning
`created_at`, `updated_at`	String	Timestamps (`updated_at` is the replication key)
`last_status_change_at`, `last_stage_change_at`, `last_action_date`	String	Status/stage change timestamps
`contact`	Object	Embedded contact summary (`id`, `name`, `company_name`, `email`, `phone`, `tags`)
`notes`, `tasks`, `calendar_events`	Array	Arrays of string identifiers or payloads from the API
`custom_fields`	Array	Array of objects (`id`, `field_value`)
`relations`	Array	Array of related records

Data Model

Relationships are driven by location scope, then CRM keys between opportunities, contacts, pipelines, and field definitions.

Use Cases for Data Analysis

Examples below use placeholder schema and table names. Replace nekt_raw and the table names with the layer and table names you configured for this source (for example nekt_raw.hilevel_opportunities).

1. Pipeline overview by stage

Summarize open opportunities by pipeline and stage using monetary_value (cast in SQL because it is stored as a string in the catalog).

SQL query

SELECT
   o.pipeline_id,
   o.pipeline_stage_id,
   o.status,
   COUNT(*) AS opportunity_count,
   SUM(TRY_CAST(o.monetary_value AS DOUBLE)) AS total_value
FROM
   nekt_raw.hilevel_opportunities o
WHERE
   o.location_id = 'YOUR_LOCATION_ID'
GROUP BY
   o.pipeline_id,
   o.pipeline_stage_id,
   o.status
ORDER BY
   total_value DESC NULLS LAST

SELECT
   o.pipeline_id,
   o.pipeline_stage_id,
   o.status,
   COUNT(*) AS opportunity_count,
   SUM(SAFE_CAST(o.monetary_value AS FLOAT64)) AS total_value
FROM
   `nekt_raw.hilevel_opportunities` o
WHERE
   o.location_id = 'YOUR_LOCATION_ID'
GROUP BY
   1,
   2,
   3
ORDER BY
   total_value DESC

Implementation Notes

Replication and state

Incremental streams partition bookmark state by location_id, so each sub-account progresses independently.
locations exists mainly to drive per-location extraction in the Singer tap; enable it in the catalog only if you want that reference table materialized.

Child streams (`notes` and `tasks`)

Replication and merging: notes and tasks are fetched individually for each contact updated in the sync window. Because these API endpoints do not accept a date filter, the connector reads all of a contact’s child records. They declare a replication key (date_added for notes, due_date for tasks) strictly to keep the extraction mode INCREMENTAL in the catalog, ensuring the data warehouse merges records on their primary keys rather than dropping data for contacts that didn’t change in the window.
Deleted contacts mid-sync: The extraction searches for updated contacts and subsequently fetches their notes/tasks. If a contact is deleted in GoHighLevel between the search and the child stream fetch, the API returns a 400 Contact not found error. The connector safely skips these deleted contacts rather than failing the overall sync.

Data shape

contacts.opportunities and some custom field values are stored as strings (JSON text) where the API returns nested structures or mixed types.
opportunities.monetary_value is modeled as a string; cast explicitly in SQL for numeric aggregations.

API usage

Selecting fewer streams reduces runtime and API load. Prefer incremental streams with a tight Start date for large locations.

Skills for agents

Download HighLevel skills file

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

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HighLevel as a data source

Configuring HighLevel as a Source

1. Add account access

2. Select streams

3. Configure data streams

4. Configure data source

5. Check your new source

Streams and Fields

Data Model

Use Cases for Data Analysis

1. Pipeline overview by stage

Implementation Notes

Replication and state

Child streams (`notes` and `tasks`)

Data shape

API usage

Skills for agents

Download HighLevel skills file

​Configuring HighLevel as a Source

​1. Add account access

​2. Select streams

​3. Configure data streams

​4. Configure data source

​5. Check your new source

​Streams and Fields

​Data Model

​Use Cases for Data Analysis

​1. Pipeline overview by stage

​Implementation Notes

​Replication and state

​Child streams (notes and tasks)

​Data shape

​API usage

​Skills for agents

Download HighLevel skills file

Configuring HighLevel as a Source

1. Add account access

2. Select streams

3. Configure data streams

4. Configure data source

5. Check your new source

Streams and Fields

Data Model

Use Cases for Data Analysis

1. Pipeline overview by stage

Implementation Notes

Replication and state

Child streams (`notes` and `tasks`)

Data shape

API usage

Skills for agents