Chargebee
The Chargebee agent connector is a Python package that equips AI agents to interact with Chargebee 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.
Connector for the Chargebee billing and subscription management API. Supports reading subscriptions, customers, invoices, credit notes, coupons, transactions, events, orders, items, item prices, and payment sources. Chargebee is a recurring billing platform that helps SaaS and subscription businesses manage the full subscription lifecycle.
Example prompts
The Chargebee connector is optimized to handle prompts like these.
- List all active subscriptions
- Show me details for a specific customer
- List recent invoices
- Show me details for a specific subscription
- List all coupons
- List recent transactions
- List recent events
- Show me customers with the highest monthly recurring revenue
- Which subscriptions are set to cancel in the next 30 days?
- List all overdue invoices and their amounts
- Analyze subscription churn trends over the past quarter
- What are the most popular items by number of subscriptions?
- Show me total revenue breakdown by currency
- Identify customers with expiring payment sources
- Compare subscription plan distribution across item prices
- List all credit notes issued in the past month
- What is the average subscription lifetime for each plan?
Unsupported prompts
The Chargebee connector isn't currently able to handle prompts like these.
- Create a new subscription in Chargebee
- Update a customer's billing address
- Cancel a subscription
- Apply a coupon to a subscription
- Issue a refund for an invoice
Entities and actions
This connector supports the following entities and actions. For more details, see this connector's full reference documentation.
| Entity | Actions |
|---|---|
| Customer | List, Get, Context Store Search |
| Subscription | List, Get, Context Store Search |
| Invoice | List, Get, Context Store Search |
| Credit Note | List, Get, Context Store Search |
| Coupon | List, Get, Context Store Search |
| Transaction | List, Get, Context Store Search |
| Event | List, Get, Context Store Search |
| Order | List, Get, Context Store Search |
| Item | List, Get, Context Store Search |
| Item Price | List, Get, Context Store Search |
| Payment Source | List, Get, Context Store Search |
Chargebee API docs
See the official Chargebee 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 ChargebeeConnector 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.chargebee import ChargebeeConnector
connector = connect("chargebee", workspace_name="<your_workspace_name>")
agent = Agent("openai:gpt-4o")
@agent.tool_plain
@ChargebeeConnector.tool_utils
async def chargebee_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.chargebee import ChargebeeConnector
connector = connect("chargebee", workspace_name="<your_workspace_name>")
@tool
@ChargebeeConnector.tool_utils
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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.chargebee import ChargebeeConnector
connector = connect("chargebee", 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)
@ChargebeeConnector.tool_utils(framework="openai_agents")
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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="Chargebee Assistant", tools=[chargebee_execute])
FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.chargebee import ChargebeeConnector
connector = connect("chargebee", workspace_name="<your_workspace_name>")
mcp = FastMCP("Chargebee Agent")
@mcp.tool
@ChargebeeConnector.tool_utils
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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.chargebee import ChargebeeConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = ChargebeeConnector(
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
@ChargebeeConnector.tool_utils
async def chargebee_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.chargebee import ChargebeeConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = ChargebeeConnector(
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
@ChargebeeConnector.tool_utils
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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.chargebee import ChargebeeConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = ChargebeeConnector(
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)
@ChargebeeConnector.tool_utils(framework="openai_agents")
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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="Chargebee Assistant", tools=[chargebee_execute])
FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.chargebee import ChargebeeConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig
connector = ChargebeeConnector(
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("Chargebee Agent")
@mcp.tool
@ChargebeeConnector.tool_utils
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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.chargebee import ChargebeeConnector
from airbyte_agent_sdk.connectors.chargebee.models import ChargebeeAuthConfig
connector = ChargebeeConnector(
auth_config=ChargebeeAuthConfig(
api_key="<Your Chargebee API key (used as the HTTP Basic username)>"
)
)
agent = Agent("openai:gpt-4o")
@agent.tool_plain
@ChargebeeConnector.tool_utils
async def chargebee_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.chargebee import ChargebeeConnector
from airbyte_agent_sdk.connectors.chargebee.models import ChargebeeAuthConfig
connector = ChargebeeConnector(
auth_config=ChargebeeAuthConfig(
api_key="<Your Chargebee API key (used as the HTTP Basic username)>"
)
)
@tool
@ChargebeeConnector.tool_utils
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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.chargebee import ChargebeeConnector
from airbyte_agent_sdk.connectors.chargebee.models import ChargebeeAuthConfig
connector = ChargebeeConnector(
auth_config=ChargebeeAuthConfig(
api_key="<Your Chargebee API key (used as the HTTP Basic username)>"
)
)
# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@ChargebeeConnector.tool_utils(framework="openai_agents")
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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="Chargebee Assistant", tools=[chargebee_execute])
FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.chargebee import ChargebeeConnector
from airbyte_agent_sdk.connectors.chargebee.models import ChargebeeAuthConfig
connector = ChargebeeConnector(
auth_config=ChargebeeAuthConfig(
api_key="<Your Chargebee API key (used as the HTTP Basic username)>"
)
)
mcp = FastMCP("Chargebee Agent")
@mcp.tool
@ChargebeeConnector.tool_utils
async def chargebee_execute(entity: str, action: str, params: dict | None = None):
"""Execute Chargebee 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: 1.0.2