Stripe
The Stripe agent connector is a Python package that equips AI agents to interact with Stripe through strongly typed, well-documented tools. It's ready to use directly in your Python app, in an agent framework, or exposed through an MCP.
Stripe is a payment processing platform that enables businesses to accept payments, manage subscriptions, and handle financial transactions. This connector provides access to customers for payment analytics and customer management.
Example prompts
The Stripe connector is optimized to handle prompts like these.
- List customers created in the last 7 days
- Show me details for a recent customer
- List recent charges
- Show me details for a recent charge
- List recent invoices
- List active subscriptions
- Create a payment intent for $50.00 USD
- Create a new invoice for customer cus_123
- Create a subscription for customer cus_123 with price price_456
- Create a price of $29.99/month for product prod_789
- Create a checkout session for price price_456
- Cancel payment intent pi_123
- Finalize invoice inv_123
- Show me my top 10 customers by total revenue this month
- List all customers who have spent over $5,000 in the last quarter
- Analyze payment trends for my Stripe customers
- Identify which customers have the most consistent subscription payments
- Give me insights into my customer retention rates
- Summarize the payment history for {customer}
- Compare customer spending patterns from last month to this month
- Show me details about my highest-value Stripe customers
- What are the key financial insights from my customer base?
- Break down my customers by their average transaction value
Unsupported prompts
The Stripe connector isn't currently able to handle prompts like these.
- Send a payment reminder to {customer}
Entities and actions
This connector supports the following entities and actions. For more details, see this connector's full reference documentation.
| Entity | Actions |
|---|---|
| Customers | List, Create, Get, Update, Delete, API Search, Context Store Search |
| Invoices | List, Create, Get, API Search, Context Store Search |
| Invoice Finalizations | Create |
| Invoice Sends | Create |
| Charges | List, Get, API Search, Context Store Search |
| Subscriptions | List, Create, Get, Update, Delete, API Search, Context Store Search |
| Refunds | List, Create, Get, Context Store Search |
| Products | List, Create, Get, Update, Delete, API Search |
| Balance | Get |
| Balance Transactions | List, Get |
| Payment Intents | List, Create, Get, Update, API Search |
| Payment Intent Confirmations | Create |
| Payment Intent Cancellations | Create |
| Prices | Create |
| Checkout Sessions | Create |
| Payment Method Attachments | Create |
| Disputes | List, Get |
| Payouts | List, Get |
Stripe API docs
See the official Stripe API reference.
SDK installation
uv pip install airbyte-agent-sdk
SDK usage
Connectors can run in hosted or open source mode.
Hosted
In hosted mode, API credentials are stored securely in Airbyte Agents. You provide your Airbyte credentials instead.
If your Airbyte client can access multiple organizations, also set organization_id.
This example assumes you've already authenticated your connector with Airbyte. See Authentication to learn more about authenticating. If you need a step-by-step guide, see the hosted execution tutorial.
The connect() factory returns a fully typed StripeConnector and reads AIRBYTE_CLIENT_ID / AIRBYTE_CLIENT_SECRET from the environment:
- Pydantic AI
- LangChain
- OpenAI Agents
- FastMCP
Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.stripe import StripeConnector
connector = connect("stripe", workspace_name="<your_workspace_name>")
agent = Agent("openai:gpt-4o")
@agent.tool_plain
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
LangChain
from langchain_core.tools import tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.stripe import StripeConnector
connector = connect("stripe", workspace_name="<your_workspace_name>")
@tool
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe 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
OpenAI Agents
from agents import Agent, function_tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.stripe import StripeConnector
connector = connect("stripe", 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)
@StripeConnector.tool_utils(framework="openai_agents")
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe 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="Stripe Assistant", tools=[stripe_execute])
FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.stripe import StripeConnector
connector = connect("stripe", workspace_name="<your_workspace_name>")
mcp = FastMCP("Stripe Agent")
@mcp.tool
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe 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
- LangChain
- OpenAI Agents
- FastMCP
Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.stripe import StripeConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = StripeConnector(
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
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
LangChain
from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.stripe import StripeConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = StripeConnector(
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
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe 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
OpenAI Agents
from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.stripe import StripeConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = StripeConnector(
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)
@StripeConnector.tool_utils(framework="openai_agents")
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe 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="Stripe Assistant", tools=[stripe_execute])
FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.stripe import StripeConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = StripeConnector(
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("Stripe Agent")
@mcp.tool
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe connector operations."""
result = await connector.execute(entity, action, params or {})
return result.model_dump(mode="json") if hasattr(result, "model_dump") else result
Open source
In open source mode, you provide API credentials directly to the connector.
- Pydantic AI
- LangChain
- OpenAI Agents
- FastMCP
Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.stripe import StripeConnector
from airbyte_agent_sdk.connectors.stripe.models import StripeAuthConfig
connector = StripeConnector(
auth_config=StripeAuthConfig(
api_key="<Your Stripe API Key (starts with sk_test_ or sk_live_)>"
)
)
agent = Agent("openai:gpt-4o")
@agent.tool_plain
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
LangChain
from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.stripe import StripeConnector
from airbyte_agent_sdk.connectors.stripe.models import StripeAuthConfig
connector = StripeConnector(
auth_config=StripeAuthConfig(
api_key="<Your Stripe API Key (starts with sk_test_ or sk_live_)>"
)
)
@tool
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe 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
OpenAI Agents
from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.stripe import StripeConnector
from airbyte_agent_sdk.connectors.stripe.models import StripeAuthConfig
connector = StripeConnector(
auth_config=StripeAuthConfig(
api_key="<Your Stripe API Key (starts with sk_test_ or sk_live_)>"
)
)
# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@StripeConnector.tool_utils(framework="openai_agents")
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe 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="Stripe Assistant", tools=[stripe_execute])
FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.stripe import StripeConnector
from airbyte_agent_sdk.connectors.stripe.models import StripeAuthConfig
connector = StripeConnector(
auth_config=StripeAuthConfig(
api_key="<Your Stripe API Key (starts with sk_test_ or sk_live_)>"
)
)
mcp = FastMCP("Stripe Agent")
@mcp.tool
@StripeConnector.tool_utils
async def stripe_execute(entity: str, action: str, params: dict | None = None):
"""Execute Stripe connector operations."""
result = await connector.execute(entity, action, params or {})
return result.model_dump(mode="json") if hasattr(result, "model_dump") else result
Authentication
For all authentication options, see the connector's authentication documentation.
Version information
Connector version: 0.1.13