Slack

Two tools: query_slack for searching and reading, update_slack for posting messages.

Complete Setup before running this example. Search needs a user token in addition to the bot token. Save as slack_context.py and run python slack_context.py:

import asyncio

from agno.agent import Agent
from agno.context.slack import SlackContextProvider
from agno.models.openai import OpenAIResponses

async def main():
    slack = SlackContextProvider(write=False, model=OpenAIResponses(id="gpt-5.4-mini"))
    agent = Agent(
        model=OpenAIResponses(id="gpt-5.4"),
        tools=slack.get_tools(),
        instructions=slack.instructions(),
    )
    await agent.aprint_response("What did the team discuss about the auth migration?")

if __name__ == "__main__":
    asyncio.run(main())

The agent can call query_slack; its sub-agent searches and reads relevant threads. This example exposes no posting tool.

When to use this vs SlackTools

Setup

In a virtual environment, install the SDKs and configure your Slack app tokens:

uv pip install -U agno openai slack-sdk aiohttp
export OPENAI_API_KEY="your-openai-api-key"
export SLACK_USER_TOKEN=xoxp-...
export SLACK_BOT_TOKEN=xoxb-...

Or pass directly: SlackContextProvider(token="xoxb-...").

Install the Slack app in your workspace with the scopes needed for search and channel/thread reads. Invite it to private channels it must read. With only a bot token, ask about a specific accessible channel or thread; full-text search is unavailable.

See SlackTools for OAuth scope requirements.

Example queries

Queries that work well give the provider a topic to search and context to narrow results:

Queries that are too vague:

Configuration

Read/write modes

Control what the agent can do:

# Research agent: can search but not post
slack = SlackContextProvider(write=False)

# Notification agent: can post but not search
slack = SlackContextProvider(read=False)

Use write=False for research, triage, audit, and eval agents. The read sub-agent physically cannot post because send_message isn't in its toolkit.

Multi-provider example

After completing Google Drive setup too, replace the body of main() with this composition fragment. Add the imports at module scope:

from agno.context.slack import SlackContextProvider
from agno.context.gdrive import GoogleDriveContextProvider

slack = SlackContextProvider(write=False)
drive = GoogleDriveContextProvider()

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4"),
    tools=[*slack.get_tools(), *drive.get_tools()],
    instructions="Use Slack for team discussion, Drive for docs. Note when they disagree.",
)

await agent.aprint_response("What's the current auth spec and did engineering raise concerns?")

The agent sees 2 tools (query_slack, query_gdrive) on the calling agent.

Tips

• Token naming: SLACK_BOT_TOKEN is preferred; SLACK_TOKEN is a fallback.
• Search: search_messages needs a user token. Set SLACK_USER_TOKEN or pass user_token=. With only a bot token, the read sub-agent uses channel history and threads.
• Private channels: The bot must be invited to access private channel history.
• Thread context: Ask for "the thread" or "the decision" to read replies rather than only the parent. The current get_thread call defaults to at most 20 messages and does not paginate.
• Channel names: Natural names like #general work. The sub-agent resolves them to IDs.
• Write clarity: "Post this to #team" is safer than vague "send it."

Resources