Installation & Usage
[01]
Install Package
Using uv or pip
BASH
uv pip install airbyte-agent-pinterest
[02]
Import
Initialize and use
PYTHON
from airbyte_agent_pinterest import PinterestConnector
from airbyte_agent_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.>"
)
)[03]
Tool
Add tools to your agent
python
@agent.tool_plain # assumes you're using Pydantic AI
@PinterestConnector.tool_utils
async def pinterest_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})Supported Entities & Actions
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| Entity | Actions |\n|--------|---------|\n| Ad Accounts | [List](./REFERENCE.md#ad-accounts-list), [Get](./REFERENCE.md#ad-accounts-get), [Search](./REFERENCE.md#ad-accounts-search) |\n| Boards | [List](./REFERENCE.md#boards-list), [Get](./REFERENCE.md#boards-get), [Search](./REFERENCE.md#boards-search) |\n| Campaigns | [List](./REFERENCE.md#campaigns-list), [Search](./REFERENCE.md#campaigns-search) |\n| Ad Groups | [List](./REFERENCE.md#ad-groups-list), [Search](./REFERENCE.md#ad-groups-search) |\n| Ads | [List](./REFERENCE.md#ads-list), [Search](./REFERENCE.md#ads-search) |\n| Board Sections | [List](./REFERENCE.md#board-sections-list), [Search](./REFERENCE.md#board-sections-search) |\n| Board Pins | [List](./REFERENCE.md#board-pins-list), [Search](./REFERENCE.md#board-pins-search) |\n| Catalogs | [List](./REFERENCE.md#catalogs-list), [Search](./REFERENCE.md#catalogs-search) |\n| Catalogs Feeds | [List](./REFERENCE.md#catalogs-feeds-list), [Search](./REFERENCE.md#catalogs-feeds-search) |\n| Catalogs Product Groups | [List](./REFERENCE.md#catalogs-product-groups-list), [Search](./REFERENCE.md#catalogs-product-groups-search) |\n| Audiences | [List](./REFERENCE.md#audiences-list), [Search](./REFERENCE.md#audiences-search) |\n| Conversion Tags | [List](./REFERENCE.md#conversion-tags-list), [Search](./REFERENCE.md#conversion-tags-search) |\n| Customer Lists | [List](./REFERENCE.md#customer-lists-list), [Search](./REFERENCE.md#customer-lists-search) |\n| Keywords | [List](./REFERENCE.md#keywords-list), [Search](./REFERENCE.md#keywords-search) |
Example Prompts
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List all my Pinterest ad accounts - List all my Pinterest boards - Show me all campaigns in my ad account - List all ads in my ad account - Show me all ad groups in my ad account - List all audiences for my ad account - Show me my catalog feeds - Which campaigns are currently active? - What are the top boards by pin count? - Show me ads that have been rejected - Find campaigns with the highest daily spend cap
Why Airbyte for AI Agents?
Built for production AI workloads with enterprise-grade reliability
Secure Authentication
Built-in OAuth 2.0 handling with automatic token refresh. No hard-coded credentials.
Agent-Native Design
Heading
Structured, LLM-friendly schemas optimized for AI agent consumption with natural language query support.
Production Ready
Battle-tested connectors with comprehensive error handling, logging, and retry logic.
Open Source
Fully open source under the MIT license. Contribute, customize, and extend freely.
Works with your favorite frameworks
LangChain
CrewAI
LlamaIndex
AutoGen
OpenAI Agents SDK
Claude Agents SDK
Frequently Asked Questions
Didn't find your answer? Please don't hesitate to reach out.
The Pinterest connector supports OAuth2 authentication. You provide a refresh token, client ID, and client secret directly in open source mode. In hosted mode, credentials are stored securely in Airbyte Cloud and you authenticate using your Airbyte client ID and client secret instead.
Can I use this connector with any AI agent framework?
The connector is compatible with any Python-based AI agent framework including LangChain, LlamaIndex, CrewAI, Pydantic AI, and custom implementations.
Does this connector support write operations?
Currently, the Pinterest connector focuses on read operations only. Write operations such as creating boards, updating campaign budgets, deleting ad groups, posting pins, or accessing analytics are not supported at this time.
How is this different from the Airbyte data connector?
Agent connectors are specifically designed for AI agents and LLM applications. They provide natural language interfaces, optimized response formats, and seamless integration with agent frameworks, unlike traditional ETL-focused connectors.
Get started in minutes with our open-source connector.