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.

Hosted mode (most cases)

In hosted mode, create the connector through the Airbyte Agent CLI or API, then execute operations using the CLI, Python SDK, or API. If you need a step-by-step guide, see the developer quickstart.

OAuth

Use the CLI for hosted OAuth connector creation when possible. It opens the hosted setup flow and avoids passing connector secrets through the command line:

airbyte-agent login
airbyte-agent connectors create --json '{
  "workspace": "<your_workspace_name>",
  "name": "slack"
}'

For API-first use cases, create a connector with OAuth credentials directly.

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.>"
    }
  }'

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 the CLI, Python SDK, or API. If your Airbyte client can access multiple organizations, set the default organization with airbyte-agent organizations use, include organization_id in AirbyteAuthConfig, or include X-Organization-Id in raw API calls.

CLI

Authenticate with Airbyte:

airbyte-agent login

Create the connector. The CLI opens the hosted setup flow:

airbyte-agent connectors create --json '{
  "workspace": "<your_workspace_name>",
  "name": "slack"
}'

Describe the connector to see its supported entities and actions:

airbyte-agent connectors describe --json '{
  "workspace": "<your_workspace_name>",
  "name": "slack"
}'

Execute an action:

airbyte-agent connectors execute --json '{
  "workspace": "<your_workspace_name>",
  "name": "slack",
  "entity": "<entity>",
  "action": "<action>",
  "params": {}
}'

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": {}}'

Open source mode

In open source mode, 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-)>"
    )
)