Serve an Agent in Slack

Mount one persistent Agent on the Slack interface.

Mount one persistent Agent on the Slack interface. Direct messages are always answered; reply_to_mentions_only only filters non-mention messages in channels.

basic.py
"""
Serve an Agent in Slack
=======================

Mount one persistent Agent on the Slack interface. Direct messages are always
answered; reply_to_mentions_only only filters non-mention messages in channels.

Prerequisites: SLACK_TOKEN, SLACK_SIGNING_SECRET, OPENAI_API_KEY
Run: .venvs/demo/bin/python cookbook/05_agent_os/17_slack/basic.py
Try in Slack: In one thread, say "My project is Cedar", then ask what the project is
Slack scopes: app_mentions:read, assistant:write, chat:write, im:history
"""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.os.interfaces.slack import Slack

# ---------------------------------------------------------------------------
# Create Slack AgentOS
# ---------------------------------------------------------------------------

db = SqliteDb(
    id="slack-basic-db",
    db_file="tmp/slack_basic.db",
)

assistant = Agent(
    id="slack-assistant",
    name="Slack Assistant",
    model=OpenAIResponses(id="gpt-5.5"),
    db=db,
    instructions=[
        "You are a helpful assistant in Slack.",
        "Keep answers concise and easy to scan.",
    ],
    add_history_to_context=True,
    num_history_runs=3,
    markdown=True,
)

agent_os = AgentOS(
    id="slack-basic-os",
    description="AgentOS serving one persistent Slack assistant.",
    agents=[assistant],
    interfaces=[
        Slack(
            agent=assistant,
            reply_to_mentions_only=True,
        )
    ],
)
app = agent_os.get_app()

# ---------------------------------------------------------------------------
# Run Slack AgentOS
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    agent_os.serve(app=app)

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Prepare the Slack app

Follow Slack setup to create and install the app, obtain its bot token and signing secret, and configure its current agent experience. Add the bot scopes listed in this example's source docstring and reinstall after changing scopes. Subscribe to app_mention and message.im; configure interactivity for buttons and forms.

Install ngrok and run ngrok http 7777 in another terminal. Keep the tunnel running. After starting this example's server, use the callback paths listed on this page under your public HTTPS URL and complete Slack's verification challenge. Configure each app separately for a multi-app example.

Streaming requires the corresponding Slack app capability. The current Agno adapter initializes suggested prompts on the legacy assistant_thread_started event; the setup guide explains the new-app limitation. Keep only one standalone example on port 7777 at a time.

Install dependencies

uv pip install -U "agno[os,slack]" openai

Export environment variables

export OPENAI_API_KEY="your_openai_api_key_here"
export SLACK_SIGNING_SECRET="your_slack_signing_secret_here"
export SLACK_TOKEN="your_slack_token_here"

Run the example

Save the code above as basic.py, then run:

python basic.py

Connect Slack to the running server

Keep Python and ngrok running. In each app's Slack settings, prepend your public HTTPS origin to these paths:

AppEvent subscriptionsInteractivity
Slack app/slack/events/slack/interactions

Complete URL verification, then send a DM or invite the app to a channel and @mention it. Ordinary channel replies require an @mention with the default configuration.

Full source: cookbook/05_agent_os/17_slack/basic.py