Slack Integration FAQs

Question 1

What are the available tools provided by this integration?

Accepted Answer

It offers a suite of tools, including: `slack_list_channels`, `slack_post_message`, `slack_reply_to_thread`, `slack_add_reaction`, `slack_get_channel_history`, `slack_get_thread_replies`, `slack_get_users`, and `slack_get_user_profile`.

Question 2

How do I set up the Slack Integration?

Accepted Answer

You need to create a Slack App in the Slack API Console, add the necessary Bot Token Scopes (channels:history, channels:read, chat:write, reactions:write, users:read, users:read.email), install the app to your workspace, and copy the Bot User OAuth Token. Finally, set the SLACK_BOT_TOKEN and SLACK_TEAM_ID environment variables.

Question 3

What does the Slack Integration tool do?

Accepted Answer

It allows AI assistants to connect to Slack workspaces and perform actions like listing channels, sending messages, retrieving history, and managing user profiles via the Model Context Protocol.

Question 4

What are the key features of this integration?

Accepted Answer

The key features include: listing Slack channels, sending messages to channels, replying to threads, adding reactions, retrieving channel history, and accessing user profiles.

Question 5

What is the Model Context Protocol (MCP)?

Accepted Answer

The Model Context Protocol (MCP) is a standardized way for AI assistants to interact with various applications, in this case, Slack. It enables seamless integration and interaction between AI models and the Slack workspace.

Slack Integration

About

Key Features

Use Cases