docs/ai-agents/connectors/intercom/README.md
The Intercom agent connector is a Python package that equips AI agents to interact with Intercom 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.
Intercom is a customer messaging platform that enables businesses to communicate with customers through chat, email, and in-app messaging. This connector provides access to core Intercom entities including contacts, conversations, companies, teams, admins, tags, and segments for customer support analytics and insights. It also supports creating and updating contacts, creating notes, creating internal articles, creating and updating companies, and creating tags.
The Intercom connector is optimized to handle prompts like these.
The Intercom connector isn't currently able to handle prompts like these.
uv pip install airbyte-agent-intercom
Connectors can run in open source or hosted mode.
In open source mode, you provide API credentials directly to the connector.
from airbyte_agent_intercom import IntercomConnector
from airbyte_agent_intercom.models import IntercomAuthConfig
connector = IntercomConnector(
auth_config=IntercomAuthConfig(
access_token="<Your Intercom API Access Token>"
)
)
@agent.tool_plain # assumes you're using Pydantic AI
@IntercomConnector.tool_utils
async def intercom_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_intercom import IntercomConnector, AirbyteAuthConfig
connector = IntercomConnector(
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
@IntercomConnector.tool_utils
async def intercom_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 |
|---|---|
| Contacts | List, Create, Get, Update, Search |
| Conversations | List, Get, Search |
| Companies | List, Create, Get, Update, Search |
| Teams | List, Get, Search |
| Admins | List, Get |
| Tags | List, Create, Get |
| Notes | Create |
| Segments | List, Get |
| Internal Articles | Create |
For all authentication options, see the connector's authentication documentation.
See the official Intercom API reference.