Slack Summarizer

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This cookbook builds a standalone Python script that connects to a Slack workspace, fetches recent messages from a channel, and summarizes the key topics, decisions, and action items. We'll use scoped sessions to limit the agent to Slack tools only.

Prerequisites

Project setup

Create a new project and install dependencies:

mkdir composio-slack-summarizer && cd composio-slack-summarizer
uv init && uv add composio composio-openai-agents openai-agents

Add your API keys to a .env file:

.env

COMPOSIO_API_KEY=your_composio_api_key
OPENAI_API_KEY=your_openai_api_key

Setting up the client

Composio takes an OpenAIAgentsProvider so that tools come back in the format the OpenAI Agents SDK expects.

from agents import Agent, Runner
from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider

composio = Composio(provider=OpenAIAgentsProvider())

Connecting to Slack

Before summarizing, we need to make sure the user has connected their Slack workspace. The connect function creates a scoped session with toolkits=["slack"] and checks the connection status via session.toolkits(). If Slack is not connected, session.authorize("slack") starts the OAuth flow and returns a URL for the user to visit. wait_for_connection() blocks until they complete it.

def connect(user_id: str):
    """Check if Slack is connected. If not, start OAuth and wait."""
    session = composio.create(user_id=user_id, toolkits=["slack"])
    toolkits = session.toolkits()

    for t in toolkits.items:
        if t.slug == "slack" and t.connection and t.connection.is_active:
            print("Slack is already connected.")
            return

    connection_request = session.authorize("slack")
    print(f"Open this URL to connect Slack:\n{connection_request.redirect_url}")
    connection_request.wait_for_connection()
    print("Connected.")

Summarizing a channel

With Slack connected, the summarize function creates a session and grabs the tools. We hand them to an agent with focused summarization instructions. Runner.run_sync handles the agentic loop: the agent calls the Slack tool to fetch messages and produces a summary.

def summarize(user_id: str, channel: str):
    """Fetch recent messages from a Slack channel and summarize them."""
    session = composio.create(user_id=user_id, toolkits=["slack"])
    tools = session.tools()

    agent = Agent(
        name="Slack Summarizer",
        instructions=(
            "You summarize Slack channel messages. "
            "Fetch recent messages from the given channel and provide a concise summary "
            "of the key topics, decisions, and action items."
        ),
        tools=tools,
    )

    result = Runner.run_sync(
        starting_agent=agent,
        input=f"Summarize the recent messages from the #{channel} channel.",
    )
    print(result.final_output)

Complete script

Here is everything together:

import sys

# region setup
from agents import Agent, Runner
from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider

composio = Composio(provider=OpenAIAgentsProvider())
# endregion setup


# region connect
def connect(user_id: str):
    """Check if Slack is connected. If not, start OAuth and wait."""
    session = composio.create(user_id=user_id, toolkits=["slack"])
    toolkits = session.toolkits()

    for t in toolkits.items:
        if t.slug == "slack" and t.connection and t.connection.is_active:
            print("Slack is already connected.")
            return

    connection_request = session.authorize("slack")
    print(f"Open this URL to connect Slack:\n{connection_request.redirect_url}")
    connection_request.wait_for_connection()
    print("Connected.")
# endregion connect


# region summarize
def summarize(user_id: str, channel: str):
    """Fetch recent messages from a Slack channel and summarize them."""
    session = composio.create(user_id=user_id, toolkits=["slack"])
    tools = session.tools()

    agent = Agent(
        name="Slack Summarizer",
        instructions=(
            "You summarize Slack channel messages. "
            "Fetch recent messages from the given channel and provide a concise summary "
            "of the key topics, decisions, and action items."
        ),
        tools=tools,
    )

    result = Runner.run_sync(
        starting_agent=agent,
        input=f"Summarize the recent messages from the #{channel} channel.",
    )
    print(result.final_output)
# endregion summarize


if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage:")
        print("  python main.py connect <user_id>")
        print("  python main.py summarize <user_id> <channel>")
        sys.exit(1)

    command = sys.argv[1]

    if command == "connect":
        user_id = sys.argv[2] if len(sys.argv) > 2 else "default"
        connect(user_id)
    elif command == "summarize":
        user_id = sys.argv[2] if len(sys.argv) > 2 else "default"
        channel = sys.argv[3] if len(sys.argv) > 3 else "general"
        summarize(user_id, channel)
    else:
        print(f"Unknown command: {command}")
        print("Use 'connect' or 'summarize'.")
        sys.exit(1)

Running the script

First, connect your Slack workspace:

uv run --env-file .env python main.py connect default

If Slack is not connected yet, you'll get an OAuth URL. Open it in your browser and authorize the app. If you've already connected, the script will print "Slack is already connected."

Then run the summarizer:

uv run --env-file .env python main.py summarize default general

Replace general with any channel name you want to summarize.