Slack authentication

This connector is optimized for AI agents. For the data replication connector, see Slack.

This page documents the authentication and configuration options for the Slack agent connector.

Authentication

Open source execution

In open source mode, you provide API credentials directly to the connector.

OAuth

credentials fields you need:

Field Name	Type	Required	Description
client_id	str	No	Your Slack App's Client ID
client_secret	str	No	Your Slack App's Client Secret
access_token	str	Yes	OAuth access token (bot token from oauth.v2.access response)

Example request:

from airbyte_agent_sdk.connectors.slack import SlackConnector
from airbyte_agent_sdk.connectors.slack.models import SlackOauth20AuthenticationAuthConfig

connector = SlackConnector(
    auth_config=SlackOauth20AuthenticationAuthConfig(
        client_id="<Your Slack App's Client ID>",
        client_secret="<Your Slack App's Client Secret>",
        access_token="<OAuth access token (bot token from oauth.v2.access response)>"
    )
)

Token

credentials fields you need:

Field Name	Type	Required	Description
bot_key	str	Yes	Your Slack Bot Key (xoxb-) or User Token (xoxp-)

Example request:

from airbyte_agent_sdk.connectors.slack import SlackConnector
from airbyte_agent_sdk.connectors.slack.models import SlackTokenAuthenticationAuthConfig

connector = SlackConnector(
    auth_config=SlackTokenAuthenticationAuthConfig(
        bot_key="<Your Slack Bot Key (xoxb-) or User Token (xoxp-)>"
    )
)

Hosted execution

In hosted mode, you first create a connector via the Airbyte Agent API (providing your OAuth or Token credentials), then execute operations using either the Python SDK or API. If you need a step-by-step guide, see the developer quickstart.

OAuth

Create a connector with OAuth credentials.

credentials fields you need:

Field Name	Type	Required	Description
client_id	str	No	Your Slack App's Client ID
client_secret	str	No	Your Slack App's Client Secret
access_token	str	Yes	OAuth access token (bot token from oauth.v2.access response)

replication_config fields you need:

Field Name	Type	Required	Description
start_date	str (date-time)	Yes	UTC date and time in the format YYYY-MM-DDTHH:mm:ssZ from which to start replicating data.
lookback_window	int	Yes	Number of days to look back when syncing data (0-365).
join_channels	bool	Yes	Whether to automatically join public channels to sync messages.
include_archived_channels	bool	Yes	Whether to include archived channels in the sync. When disabled (default), archived channels are excluded from the Slack API response, reducing the number of API calls for downstream streams such as channel_messages, threads, and channel_members.
threads_ignore_no_replies	bool	Yes	When enabled, the threads stream will skip messages that have no replies, reducing the number of API calls. Disabled by default to make the Threads stream contain unthreaded messages in its records.

Example request:

curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors" \
  -H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_name": "<WORKSPACE_NAME>",
    "connector_type": "Slack",
    "name": "My Slack Connector",
    "credentials": {
      "client_id": "<Your Slack App's Client ID>",
      "client_secret": "<Your Slack App's Client Secret>",
      "access_token": "<OAuth access token (bot token from oauth.v2.access response)>"
    },
    "replication_config": {
      "start_date": "<UTC date and time in the format YYYY-MM-DDTHH:mm:ssZ from which to start replicating data.>",
      "lookback_window": "<Number of days to look back when syncing data (0-365).>",
      "join_channels": "<Whether to automatically join public channels to sync messages.>",
      "include_archived_channels": "<Whether to include archived channels in the sync. When disabled (default), archived channels are excluded from the Slack API response, reducing the number of API calls for downstream streams such as channel_messages, threads, and channel_members.>",
      "threads_ignore_no_replies": "<When enabled, the threads stream will skip messages that have no replies, reducing the number of API calls. Disabled by default to make the Threads stream contain unthreaded messages in its records.>"
    }
  }'

Bring your own OAuth flow

To implement your own OAuth flow, use Airbyte's server-side OAuth API endpoints. For a complete guide, see Build your own OAuth flow.

Step 1: Initiate the OAuth flow

Request a consent URL for your user.

Field Name	Type	Required	Description
workspace_name	string	Yes	Your unique identifier for the workspace
connector_type	string	Yes	The connector type (e.g., "Slack")
redirect_url	string	Yes	URL to redirect to after OAuth authorization

Example request:

curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors/oauth/initiate" \
  -H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_name": "<WORKSPACE_NAME>",
    "connector_type": "Slack",
    "redirect_url": "https://yourapp.com/oauth/callback"
  }'

Redirect your user to the consent_url from the response.

Step 2: Handle the callback

After the user authorizes access, Airbyte automatically creates the connector and redirects them to your redirect_url with a connector_id query parameter. You don't need to make a separate API call to create the connector.

https://yourapp.com/oauth/callback?connector_id=<connector_id>

Extract the connector_id from the callback URL and store it for future operations. For error handling and a complete implementation example, see Build your own OAuth flow.

Token

Create a connector with Token credentials.

credentials fields you need:

Field Name	Type	Required	Description
bot_key	str	Yes	Your Slack Bot Key (xoxb-) or User Token (xoxp-)

replication_config fields you need:

Field Name	Type	Required	Description
start_date	str (date-time)	Yes	UTC date and time in the format YYYY-MM-DDTHH:mm:ssZ from which to start replicating data.
lookback_window	int	Yes	Number of days to look back when syncing data (0-365).
join_channels	bool	Yes	Whether to automatically join public channels to sync messages.
include_archived_channels	bool	Yes	Whether to include archived channels in the sync. When disabled (default), archived channels are excluded from the Slack API response, reducing the number of API calls for downstream streams such as channel_messages, threads, and channel_members.
threads_ignore_no_replies	bool	Yes	When enabled, the threads stream will skip messages that have no replies, reducing the number of API calls. Disabled by default to make the Threads stream contain unthreaded messages in its records.

Example request:

curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors" \
  -H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_name": "<WORKSPACE_NAME>",
    "connector_type": "Slack",
    "name": "My Slack Connector",
    "credentials": {
      "bot_key": "<Your Slack Bot Key (xoxb-) or User Token (xoxp-)>"
    },
    "replication_config": {
      "start_date": "<UTC date and time in the format YYYY-MM-DDTHH:mm:ssZ from which to start replicating data.>",
      "lookback_window": "<Number of days to look back when syncing data (0-365).>",
      "join_channels": "<Whether to automatically join public channels to sync messages.>",
      "include_archived_channels": "<Whether to include archived channels in the sync. When disabled (default), archived channels are excluded from the Slack API response, reducing the number of API calls for downstream streams such as channel_messages, threads, and channel_members.>",
      "threads_ignore_no_replies": "<When enabled, the threads stream will skip messages that have no replies, reducing the number of API calls. Disabled by default to make the Threads stream contain unthreaded messages in its records.>"
    }
  }'

Execution

After creating the connector, execute operations using either the Python SDK or API. If your Airbyte client can access multiple organizations, include organization_id in AirbyteAuthConfig and X-Organization-Id in raw API calls.

Python SDK

The connect() factory returns a fully typed SlackConnector and reads AIRBYTE_CLIENT_ID / AIRBYTE_CLIENT_SECRET from the environment:

Pydantic AI

Pydantic AI

from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.slack import SlackConnector

connector = connect("slack", workspace_name="<your_workspace_name>")

agent = Agent("openai:gpt-4o")

@agent.tool_plain
@SlackConnector.tool_utils
async def slack_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

LangChain

LangChain

from langchain_core.tools import tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.slack import SlackConnector

connector = connect("slack", workspace_name="<your_workspace_name>")

@tool
@SlackConnector.tool_utils
async def slack_execute(entity: str, action: str, params: dict | None = None):
    """Execute Slack 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

OpenAI Agents

from agents import Agent, function_tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.slack import SlackConnector

connector = connect("slack", 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)
@SlackConnector.tool_utils(framework="openai_agents")
async def slack_execute(entity: str, action: str, params: dict | None = None):
    """Execute Slack 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="Slack Assistant", tools=[slack_execute])

FastMCP

FastMCP

from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.slack import SlackConnector

connector = connect("slack", workspace_name="<your_workspace_name>")

mcp = FastMCP("Slack Agent")

@mcp.tool
@SlackConnector.tool_utils
async def slack_execute(entity: str, action: str, params: dict | None = None):
    """Execute Slack 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

Pydantic AI

Pydantic AI

from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.slack import SlackConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SlackConnector(
    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
@SlackConnector.tool_utils
async def slack_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

LangChain

LangChain

from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.slack import SlackConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SlackConnector(
    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
@SlackConnector.tool_utils
async def slack_execute(entity: str, action: str, params: dict | None = None):
    """Execute Slack 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

OpenAI Agents

from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.slack import SlackConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SlackConnector(
    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)
@SlackConnector.tool_utils(framework="openai_agents")
async def slack_execute(entity: str, action: str, params: dict | None = None):
    """Execute Slack 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="Slack Assistant", tools=[slack_execute])

FastMCP

FastMCP

from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.slack import SlackConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SlackConnector(
    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("Slack Agent")

@mcp.tool
@SlackConnector.tool_utils
async def slack_execute(entity: str, action: str, params: dict | None = None):
    """Execute Slack connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

API

curl -X POST 'https://api.airbyte.ai/api/v1/integrations/connectors/<connector_id>/execute' \
  -H 'Authorization: Bearer <YOUR_BEARER_TOKEN>' \
  -H 'X-Organization-Id: <YOUR_ORGANIZATION_ID>' \
  -H 'Content-Type: application/json' \
  -d '{"entity": "<entity>", "action": "<action>", "params": {}}'