docs/ai-agents/connectors/slack/README.md
The Slack agent connector is a Python package that equips AI agents to interact with Slack 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.
Slack is a business communication platform that offers messaging, file sharing, and integrations with other tools. This connector provides read access to users, channels, channel members, channel messages, and threads for workspace analytics. It also supports write operations including sending and updating messages, creating and renaming channels, setting channel topics and purposes, and adding reactions to messages.
The Slack connector is optimized to handle prompts like these.
The Slack connector isn't currently able to handle prompts like these.
uv pip install airbyte-agent-slack
Connectors can run in open source or hosted mode.
In open source mode, you provide API credentials directly to the connector.
from airbyte_agent_slack import SlackConnector
from airbyte_agent_slack.models import SlackTokenAuthenticationAuthConfig
connector = SlackConnector(
auth_config=SlackTokenAuthenticationAuthConfig(
api_token="<Your Slack Bot Token (xoxb-) or User Token (xoxp-)>"
)
)
@agent.tool_plain # assumes you're using Pydantic AI
@SlackConnector.tool_utils
async def slack_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_slack import SlackConnector, AirbyteAuthConfig
connector = SlackConnector(
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
@SlackConnector.tool_utils
async def slack_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 |
|---|---|
| Users | List, Get, Search |
| Channels | List, Get, Create, Update, Search |
| Channel Messages | List |
| Threads | List |
| Messages | Create, Update |
| Channel Topics | Create |
| Channel Purposes | Create |
| Reactions | Create |
For all authentication options, see the connector's authentication documentation.
See the official Slack API reference.