slack-mcp
Allows interaction with Slack workspaces, including reading messages, posting content, managing channels, adding reactions, sending DMs, and executing Slack commands.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@slack-mcpsummarize today's messages in #general"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
slack-mcp
A Model Context Protocol (MCP) server that enables AI assistants to interact with Slack workspaces. This server provides a bridge between AI tools and Slack, allowing you to read messages, post content, and manage Slack channels programmatically through MCP-compatible clients.
What is this and why should I use it?
This MCP server transforms your Slack workspace into an AI-accessible environment. It provides 21+ tools for comprehensive Slack interaction:
Message & Thread Operations
Read channel history with date filtering and thread support
Post messages and replies to threads
Search messages across workspace or within specific channels
Execute Slack commands
Channel Management
List, join, create, and rename channels
Look up channel IDs by name
Invite users to channels
Reactions & Users
Add and view emoji reactions
Send direct messages and group DMs
Manage usergroups (clear members)
Utility
Check authentication status
Cache management for performance
Key Benefits
Seamless Integration: Connect your AI assistant directly to Slack without manual copy-pasting
Automated Workflows: Build AI-powered Slack bots that can read, analyze, and respond to messages
Enhanced Productivity: Let AI help manage notifications, summarize conversations, or automate routine Slack tasks
Real-time Collaboration: Enable AI assistants to participate in team discussions and provide instant insights
Use Cases
Team Assistant: Have an AI that can read team updates and provide summaries
Notification Manager: Automatically categorize and respond to incoming messages
Knowledge Base: AI that can search through channel history and provide context
Meeting Scheduler: AI that can read meeting requests and help coordinate schedules
Related MCP server: Slack MCP Server
Setting Up with Claude Code
This repo ships as a Claude Code plugin with a guided setup skill. Claude will walk you through the entire process — no manual config editing required.
Run the setup script. It handles everything — venv, Playwright, token extraction, wrapper script, and Claude Code registration. The only interaction required is logging in to Slack when the browser opens, and entering an optional channel ID for server logs, if desired.
python3 <(curl -fsSL https://raw.githubusercontent.com/redhat-community-ai-tools/slack-mcp/main/scripts/setup-slack-mcp.py)Or clone the repo first and run it locally:
git clone https://github.com/redhat-community-ai-tools/slack-mcp
python3 slack-mcp/scripts/setup-slack-mcp.pyOptions:
Flag | Description |
| Slack channel ID for server logs (optional; logs go to stderr if omitted) |
| Specific Slack workspace to open |
| Re-extract tokens when they expire (skips all other steps) |
| Skip the post-setup smoke test |
When tokens expire, just run:
python3 slack-mcp/scripts/setup-slack-mcp.py --refresh-tokensDesktop App Token Refresh (Linux)
If you have the Slack desktop app installed, you can refresh tokens without opening a browser:
slack-mcp/scripts/slack-refresh-tokens --validateThis reads tokens directly from the desktop app's local storage on disk — no DevTools, no Playwright, no manual steps. Requires the Slack app to be signed in.
Flag | Description |
| Verify tokens against Slack's API after extraction |
| Print tokens as env vars to stdout (for piping into other tools) |
| Write tokens to a custom path (default: |
Requirements: python3, python3-cryptography, secret-tool (libsecret/gnome-keyring), curl, jq
This is useful for CI hooks or session startup scripts that need to silently refresh tokens before launching the MCP server.
Bot token authentication (recommended)
For better security, use a Slack App bot token (xoxb-) instead of browser session tokens. Bot tokens provide:
Scoped access — only the OAuth permissions you grant, not full user access
Distinct identity — actions appear as the bot, not as your user account
Central management — IT can audit and revoke via the Slack admin panel
No browser DevTools — tokens are generated once in the Slack App settings
Setup
Create a Slack App at api.slack.com/apps
Add OAuth scopes:
channels:read,channels:history,channels:manage,groups:read,groups:history,groups:write,chat:write,reactions:read,reactions:write,search:read,users:read,commands,mpim:writeInstall to your workspace and copy the Bot User OAuth Token (
xoxb-...)Invite the bot to channels it needs access to
Running with a bot token
Set SLACK_BOT_TOKEN instead of SLACK_XOXC_TOKEN/SLACK_XOXD_TOKEN:
{
"mcpServers": {
"slack": {
"command": "podman",
"args": [
"run", "-i", "--rm",
"-e", "SLACK_BOT_TOKEN",
"-e", "LOGS_CHANNEL_ID",
"quay.io/redhat-ai-tools/slack-mcp"
],
"env": {
"SLACK_BOT_TOKEN": "xoxb-...",
"LOGS_CHANNEL_ID": "C7000000"
}
}
}
}LOGS_CHANNEL_ID is optional. When omitted, tool activity is written to stderr instead of posted to Slack.
If both SLACK_BOT_TOKEN and SLACK_XOXC_TOKEN/SLACK_XOXD_TOKEN are set, the bot token takes precedence.
Read-only mode
For agents or automation that should browse and search Slack without posting, reacting, running commands, or joining channels, enable read-only mode.
Environment variable: set
SLACK_MCP_READ_ONLYto a truthy value (1,true,yes, oron, case-insensitive).CLI: pass
--read-onlywhen startingslack_mcp_server.py(equivalent to setting the variable).
In read-only mode, tools that mutate Slack state (post_message, send_dm, post_command, add_reaction, join_channel) raise a clear error. Read tools (history, search, threads, whoami, channel listing, cache refresh helpers, and so on) behave as usual. Tool activity that would normally be mirrored to LOGS_CHANNEL_ID is written to stderr instead.
On startup, the server logs a line to stderr when read-only mode is active.
For Podman or Docker, add -e SLACK_MCP_READ_ONLY=true (and the matching key in env) when you want the container to run read-only.
Running with Podman or Docker
You can run the slack-mcp server in a container using Podman or Docker:
Example configuration for running with Podman:
{
"mcpServers": {
"slack": {
"command": "podman",
"args": [
"run",
"-i",
"--rm",
"-e", "SLACK_XOXC_TOKEN",
"-e", "SLACK_XOXD_TOKEN",
"-e", "MCP_TRANSPORT",
"-e", "LOGS_CHANNEL_ID",
"quay.io/redhat-ai-tools/slack-mcp"
],
"env": {
"SLACK_XOXC_TOKEN": "xoxc-...",
"SLACK_XOXD_TOKEN": "xoxd-...",
"MCP_TRANSPORT": "stdio",
"LOGS_CHANNEL_ID": "C7000000"
}
}
}
}LOGS_CHANNEL_ID is optional. When omitted, tool activity is written to stderr instead of posted to Slack.
Activity logging
By default, tool activity is written to stderr (visible in your terminal or process logs). To mirror activity to a Slack channel instead, set LOGS_CHANNEL_ID to any channel the bot or session user has access to — a self-DM or a DM with Slackbot works well for personal use.
LOGS_CHANNEL_ID=C7000000In read-only mode, LOGS_CHANNEL_ID is ignored and all activity is always written to stderr.
Running with non-stdio transport
To run the server with a non-stdio transport (such as SSE), set the MCP_TRANSPORT environment variable to a value other than stdio (e.g., sse).
Example configuration to connect to a non-stdio MCP server:
{
"mcpServers": {
"slack": {
"url": "https://slack-mcp.example.com/sse",
"headers": {
"X-Slack-Web-Token": "xoxc-...",
"X-Slack-Cookie-Token": "xoxd-..."
}
}
}
}Extract your Slack XOXC and XOXD tokens easily using browser extensions or Selenium automation: https://github.com/maorfr/slack-token-extractor.
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