docs/ai-agents/connectors/zendesk-talk/README.md
The Zendesk-Talk agent connector is a Python package that equips AI agents to interact with Zendesk-Talk 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 Zendesk Talk (Voice) API. Provides access to phone numbers, addresses, greetings, IVR configurations, call data, and agent/account statistics for Zendesk Talk voice support channels.
The Zendesk-Talk connector is optimized to handle prompts like these.
The Zendesk-Talk connector isn't currently able to handle prompts like these.
uv pip install airbyte-agent-zendesk-talk
Connectors can run in open source or hosted mode.
In open source mode, you provide API credentials directly to the connector.
from airbyte_agent_zendesk_talk import ZendeskTalkConnector
from airbyte_agent_zendesk_talk.models import ZendeskTalkApiTokenAuthConfig
connector = ZendeskTalkConnector(
auth_config=ZendeskTalkApiTokenAuthConfig(
email="<Your Zendesk account email address>",
api_token="<Your Zendesk API token from Admin Center>"
)
)
@agent.tool_plain # assumes you're using Pydantic AI
@ZendeskTalkConnector.tool_utils
async def zendesk_talk_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
In hosted mode, API credentials are stored securely in Airbyte Cloud. 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.
from airbyte_agent_zendesk_talk import ZendeskTalkConnector, AirbyteAuthConfig
connector = ZendeskTalkConnector(
auth_config=AirbyteAuthConfig(
customer_name="<your_customer_name>",
organization_id="<your_organization_id>", # Optional for multi-org clients
airbyte_client_id="<your-client-id>",
airbyte_client_secret="<your-client-secret>"
)
)
@agent.tool_plain # assumes you're using Pydantic AI
@ZendeskTalkConnector.tool_utils
async def zendesk_talk_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
This connector supports the following entities and actions. For more details, see this connector's full reference documentation.
| Entity | Actions |
|---|---|
| Phone Numbers | List, Get, Search |
| Addresses | List, Get, Search |
| Greetings | List, Get, Search |
| Greeting Categories | List, Get, Search |
| Ivrs | List, Get, Search |
| Agents Activity | List, Search |
| Agents Overview | List, Search |
| Account Overview | List, Search |
| Current Queue Activity | List, Search |
| Calls | List, Search |
| Call Legs | List, Search |
For all authentication options, see the connector's authentication documentation.
See the official Zendesk-Talk API reference.