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Pinterest authentication

This page documents the authentication and configuration options for the Pinterest agent connector.

Hosted mode (most cases)​

In hosted mode, create the connector through the Airbyte Agent CLI or API, then execute operations using the CLI, Python SDK, or API. If you need a step-by-step guide, see the developer quickstart.

OAuth​

Use the CLI for hosted OAuth connector creation when possible. It opens the hosted setup flow and avoids passing connector secrets through the command line:

airbyte-agent login
airbyte-agent connectors create --json '{
"workspace": "<your_workspace_name>",
"name": "pinterest"
}'

For API-first use cases, create a connector with OAuth credentials directly.

credentials fields you need:

Field NameTypeRequiredDescription
refresh_tokenstrYesPinterest OAuth2 refresh token.
client_idstrYesPinterest OAuth2 client ID.
client_secretstrYesPinterest OAuth2 client secret.

replication_config fields you need:

Field NameTypeRequiredDescription
start_datestrNoA date in the format YYYY-MM-DD. If not set, defaults to 89 days ago.

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": "Pinterest",
"name": "My Pinterest Connector",
"credentials": {
"refresh_token": "<Pinterest OAuth2 refresh token.>",
"client_id": "<Pinterest OAuth2 client ID.>",
"client_secret": "<Pinterest OAuth2 client secret.>"
},
"replication_config": {
"start_date": "<A date in the format YYYY-MM-DD. If not set, defaults to 89 days ago.>"
}
}'

Token​

This authentication method isn't available for this connector.

Execution​

After creating the connector, execute operations using the CLI, Python SDK, or API. If your Airbyte client can access multiple organizations, set the default organization with airbyte-agent organizations use, include organization_id in AirbyteAuthConfig, or include X-Organization-Id in raw API calls.

CLI

Authenticate with Airbyte:

airbyte-agent login

Create the connector. The CLI opens the hosted setup flow:

airbyte-agent connectors create --json '{
"workspace": "<your_workspace_name>",
"name": "pinterest"
}'

Describe the connector to see its supported entities and actions:

airbyte-agent connectors describe --json '{
"workspace": "<your_workspace_name>",
"name": "pinterest"
}'

Execute an action:

airbyte-agent connectors execute --json '{
"workspace": "<your_workspace_name>",
"name": "pinterest",
"entity": "<entity>",
"action": "<action>",
"params": {}
}'

Python SDK

The connect() factory returns a fully typed PinterestConnector and reads AIRBYTE_CLIENT_ID / AIRBYTE_CLIENT_SECRET from the environment:

The recommended pattern is build_connector_tools, which gives the agent three tools bound to this connector: inspect_connector, read_skill_docs, and execute. The agent can inspect the connector, read only the skill-doc section it needs, and then execute:

inspect_connector() -> read_skill_docs() -> read_skill_docs(section="...") -> execute(entity, action, params)
Pydantic AI
from airbyte_agent_sdk import build_connector_tools
from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.pinterest import PinterestConnector

connector = connect("pinterest", workspace_name="<your_workspace_name>")

tools = build_connector_tools(connector, framework="pydantic_ai")
agent = Agent("openai:gpt-4o", tools=tools.as_list())

Legacy alternatives​

These examples are kept for existing integrations. For new agents, use build_connector_tools above. The legacy PinterestConnector.tool_utils pattern loads the connector's full generated catalog into one broad execute tool description instead of letting the agent read skill docs on demand.

Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.pinterest import PinterestConnector

connector = connect("pinterest", workspace_name="<your_workspace_name>")

agent = Agent("openai:gpt-4o")

@agent.tool_plain
@PinterestConnector.tool_utils
async def pinterest_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})

Or pass credentials explicitly (equivalent, useful when you're not loading them from the environment):

Pydantic AI
from airbyte_agent_sdk import build_connector_tools
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.pinterest import PinterestConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = PinterestConnector(
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>"
)
)

tools = build_connector_tools(connector, framework="pydantic_ai")
agent = Agent("openai:gpt-4o", tools=tools.as_list())

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": {}}'

Open source mode​

In open source mode, provide API credentials directly to the connector.

OAuth​

credentials fields you need:

Field NameTypeRequiredDescription
refresh_tokenstrYesPinterest OAuth2 refresh token.
client_idstrYesPinterest OAuth2 client ID.
client_secretstrYesPinterest OAuth2 client secret.

Example request:

from airbyte_agent_sdk.connectors.pinterest import PinterestConnector
from airbyte_agent_sdk.connectors.pinterest.models import PinterestAuthConfig

connector = PinterestConnector(
auth_config=PinterestAuthConfig(
refresh_token="<Pinterest OAuth2 refresh token.>",
client_id="<Pinterest OAuth2 client ID.>",
client_secret="<Pinterest OAuth2 client secret.>"
)
)

Token​

This authentication method isn't available for this connector.