Hubspot authentication
This page documents the authentication and configuration options for the Hubspot agent connector.
Authentication
Open source execution
In open source mode, you provide API credentials directly to the connector.
OAuth
credentials fields you need:
| Field Name | Type | Required | Description |
|---|---|---|---|
client_id | str | No | Your HubSpot OAuth2 Client ID |
client_secret | str | No | Your HubSpot OAuth2 Client Secret |
refresh_token | str | Yes | Your HubSpot OAuth2 Refresh Token |
access_token | str | No | Your HubSpot OAuth2 Access Token (optional if refresh_token is provided) |
Example request:
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
from airbyte_agent_sdk.connectors.hubspot.models import HubspotOauth2AuthConfig
connector = HubspotConnector(
auth_config=HubspotOauth2AuthConfig(
client_id="<Your HubSpot OAuth2 Client ID>",
client_secret="<Your HubSpot OAuth2 Client Secret>",
refresh_token="<Your HubSpot OAuth2 Refresh Token>",
access_token="<Your HubSpot OAuth2 Access Token (optional if refresh_token is provided)>"
)
)
Token
credentials fields you need:
| Field Name | Type | Required | Description |
|---|---|---|---|
private_app_token | str | Yes | Access token from a HubSpot Private App |
Example request:
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
from airbyte_agent_sdk.connectors.hubspot.models import HubspotPrivateAppAuthConfig
connector = HubspotConnector(
auth_config=HubspotPrivateAppAuthConfig(
private_app_token="<Access token from a HubSpot Private App>"
)
)
Hosted execution
In hosted mode, you first create a connector via the Airbyte Agent API (providing your OAuth or Token credentials), then execute operations using either the Python SDK or API. If you need a step-by-step guide, see the developer quickstart.
OAuth
Create a connector with OAuth credentials.
credentials fields you need:
| Field Name | Type | Required | Description |
|---|---|---|---|
client_id | str | No | Your HubSpot OAuth2 Client ID |
client_secret | str | No | Your HubSpot OAuth2 Client Secret |
refresh_token | str | Yes | Your HubSpot OAuth2 Refresh Token |
access_token | str | No | Your HubSpot OAuth2 Access Token (optional if refresh_token is provided) |
Example request:
curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors" \
-H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
-H "Content-Type: application/json" \
-d '{
"workspace_name": "<WORKSPACE_NAME>",
"connector_type": "Hubspot",
"name": "My Hubspot Connector",
"credentials": {
"client_id": "<Your HubSpot OAuth2 Client ID>",
"client_secret": "<Your HubSpot OAuth2 Client Secret>",
"refresh_token": "<Your HubSpot OAuth2 Refresh Token>",
"access_token": "<Your HubSpot OAuth2 Access Token (optional if refresh_token is provided)>"
}
}'
Bring your own OAuth flow
To implement your own OAuth flow, use Airbyte's server-side OAuth API endpoints. For a complete guide, see Build your own OAuth flow.
Configure your own OAuth app credentials (optional)
By default, Airbyte uses its own OAuth app credentials. You can override these with your own so that OAuth consent screens show your company's branding. If you skip this step, the consent screen shows "Airbyte" as the requesting application.
curl -X PUT "https://api.airbyte.ai/api/v1/oauth/credentials" \
-H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
-H "Content-Type: application/json" \
-d '{
"connector_type": "hubspot",
"configuration": {
"client_id": "<Your HubSpot OAuth app's client ID>",
"client_secret": "<Your HubSpot OAuth app's client secret>"
}
}'
To revert to Airbyte-managed defaults:
curl -X DELETE "https://api.airbyte.ai/api/v1/oauth/credentials/connector_type/hubspot" \
-H "Authorization: Bearer <YOUR_BEARER_TOKEN>"
Step 1: Initiate the OAuth flow
Request a consent URL for your user.
| Field Name | Type | Required | Description |
|---|---|---|---|
workspace_name | string | Yes | Your unique identifier for the workspace |
connector_type | string | Yes | The connector type (e.g., "Hubspot") |
redirect_url | string | Yes | URL to redirect to after OAuth authorization |
Example request:
curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors/oauth/initiate" \
-H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
-H "Content-Type: application/json" \
-d '{
"workspace_name": "<WORKSPACE_NAME>",
"connector_type": "Hubspot",
"redirect_url": "https://yourapp.com/oauth/callback"
}'
Redirect your user to the consent_url from the response.
Step 2: Handle the callback
After the user authorizes access, Airbyte automatically creates the connector and redirects them to your redirect_url with a connector_id query parameter. You don't need to make a separate API call to create the connector.
https://yourapp.com/oauth/callback?connector_id=<connector_id>
Extract the connector_id from the callback URL and store it for future operations. For error handling and a complete implementation example, see Build your own OAuth flow.
Token
Create a connector with Token credentials.
credentials fields you need:
| Field Name | Type | Required | Description |
|---|---|---|---|
private_app_token | str | Yes | Access token from a HubSpot Private App |
Example request:
curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors" \
-H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
-H "Content-Type: application/json" \
-d '{
"workspace_name": "<WORKSPACE_NAME>",
"connector_type": "Hubspot",
"name": "My Hubspot Connector",
"credentials": {
"private_app_token": "<Access token from a HubSpot Private App>"
}
}'
Execution
After creating the connector, execute operations using either the Python SDK or API.
If your Airbyte client can access multiple organizations, include organization_id in AirbyteAuthConfig and X-Organization-Id in raw API calls.
Python SDK
The connect() factory returns a fully typed HubspotConnector and reads AIRBYTE_CLIENT_ID / AIRBYTE_CLIENT_SECRET from the environment:
- Pydantic AI
- LangChain
- OpenAI Agents
- FastMCP
from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
connector = connect("hubspot", workspace_name="<your_workspace_name>")
agent = Agent("openai:gpt-4o")
@agent.tool_plain
@HubspotConnector.tool_utils
async def hubspot_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
from langchain_core.tools import tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
connector = connect("hubspot", workspace_name="<your_workspace_name>")
@tool
@HubspotConnector.tool_utils
async def hubspot_execute(entity: str, action: str, params: dict | None = None):
"""Execute Hubspot connector operations."""
result = await connector.execute(entity, action, params or {})
# connector.execute returns a Pydantic envelope for typed actions; fall back to raw data otherwise.
return result.model_dump(mode="json") if hasattr(result, "model_dump") else result
from agents import Agent, function_tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
connector = connect("hubspot", workspace_name="<your_workspace_name>")
# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@HubspotConnector.tool_utils(framework="openai_agents")
async def hubspot_execute(entity: str, action: str, params: dict | None = None):
"""Execute Hubspot connector operations."""
result = await connector.execute(entity, action, params or {})
return result.model_dump(mode="json") if hasattr(result, "model_dump") else result
agent = Agent(name="Hubspot Assistant", tools=[hubspot_execute])
from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
connector = connect("hubspot", workspace_name="<your_workspace_name>")
mcp = FastMCP("Hubspot Agent")
@mcp.tool
@HubspotConnector.tool_utils
async def hubspot_execute(entity: str, action: str, params: dict | None = None):
"""Execute Hubspot connector operations."""
result = await connector.execute(entity, action, params or {})
return result.model_dump(mode="json") if hasattr(result, "model_dump") else result
Or pass credentials explicitly (equivalent, useful when you're not loading them from the environment): Pydantic AI
- Pydantic AI
- LangChain
- OpenAI Agents
- FastMCP
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = HubspotConnector(
auth_config=AirbyteAuthConfig(
workspace_name="<your_workspace_name>",
organization_id="<your_organization_id>", # Optional for multi-org clients
airbyte_client_id="<your-client-id>",
airbyte_client_secret="<your-client-secret>"
)
)
agent = Agent("openai:gpt-4o")
@agent.tool_plain
@HubspotConnector.tool_utils
async def hubspot_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = HubspotConnector(
auth_config=AirbyteAuthConfig(
workspace_name="<your_workspace_name>",
organization_id="<your_organization_id>", # Optional for multi-org clients
airbyte_client_id="<your-client-id>",
airbyte_client_secret="<your-client-secret>"
)
)
@tool
@HubspotConnector.tool_utils
async def hubspot_execute(entity: str, action: str, params: dict | None = None):
"""Execute Hubspot connector operations."""
result = await connector.execute(entity, action, params or {})
# connector.execute returns a Pydantic envelope for typed actions; fall back to raw data otherwise.
return result.model_dump(mode="json") if hasattr(result, "model_dump") else result
from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = HubspotConnector(
auth_config=AirbyteAuthConfig(
workspace_name="<your_workspace_name>",
organization_id="<your_organization_id>", # Optional for multi-org clients
airbyte_client_id="<your-client-id>",
airbyte_client_secret="<your-client-secret>"
)
)
# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@HubspotConnector.tool_utils(framework="openai_agents")
async def hubspot_execute(entity: str, action: str, params: dict | None = None):
"""Execute Hubspot connector operations."""
result = await connector.execute(entity, action, params or {})
return result.model_dump(mode="json") if hasattr(result, "model_dump") else result
agent = Agent(name="Hubspot Assistant", tools=[hubspot_execute])
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.hubspot import HubspotConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = HubspotConnector(
auth_config=AirbyteAuthConfig(
workspace_name="<your_workspace_name>",
organization_id="<your_organization_id>", # Optional for multi-org clients
airbyte_client_id="<your-client-id>",
airbyte_client_secret="<your-client-secret>"
)
)
mcp = FastMCP("Hubspot Agent")
@mcp.tool
@HubspotConnector.tool_utils
async def hubspot_execute(entity: str, action: str, params: dict | None = None):
"""Execute Hubspot connector operations."""
result = await connector.execute(entity, action, params or {})
return result.model_dump(mode="json") if hasattr(result, "model_dump") else result
API
curl -X POST 'https://api.airbyte.ai/api/v1/integrations/connectors/<connector_id>/execute' \
-H 'Authorization: Bearer <YOUR_BEARER_TOKEN>' \
-H 'X-Organization-Id: <YOUR_ORGANIZATION_ID>' \
-H 'Content-Type: application/json' \
-d '{"entity": "<entity>", "action": "<action>", "params": {}}'