Slack MCP Server

Slack MCP Server

Enables AI assistants to interact with Slack workspaces through the Model Context Protocol, providing tools for reading/sending messages, managing channels, and accessing Slack API functionality.

Category
Visit Server

README

Slack MCP Server

A Model Context Protocol (MCP) server that enables AI assistants to interact with Slack workspaces. This server provides tools for reading messages, posting messages, managing channels, and more through the Slack API.

Features

  • Channel Management: List channels, get channel info, create channels
  • Message Operations: Send messages, read message history, reply to threads
  • User Management: Get user information, list workspace members
  • File Operations: Upload files, share files in channels
  • Search: Search messages and files across the workspace
  • Reactions: Add and remove emoji reactions to messages

Prerequisites

  • Python 3.8 or higher
  • A Slack workspace with admin permissions
  • Slack Bot Token with appropriate scopes

Installation

  1. Clone this repository:
git clone <repository-url>
cd slack-mcp-server
  1. Install dependencies:
pip install -r requirements.txt
  1. Set up your Slack Bot Token (see Configuration section below)

Configuration

Setting up Slack Bot Token

  1. Go to Slack API and create a new app

  2. Navigate to "OAuth & Permissions" in the sidebar

  3. Add the following Bot Token Scopes:

    • channels:read - View basic information about public channels
    • channels:write - Manage public channels
    • chat:write - Send messages as the bot
    • chat:write.public - Send messages to channels the bot isn't a member of
    • files:read - View files shared in channels and conversations
    • files:write - Upload, edit, and delete files
    • groups:read - View basic information about private channels
    • im:read - View basic information about direct messages
    • mpim:read - View basic information about group direct messages
    • reactions:read - View emoji reactions and their associated content
    • reactions:write - Add and edit emoji reactions
    • search:read - Search messages and files
    • users:read - View people in the workspace
    • channels:history - View messages and other content in public channels
    • groups:history - View messages and other content in private channels
    • im:history - View messages and other content in direct messages
    • mpim:history - View messages and other content in group direct messages
  4. Install the app to your workspace

  5. Copy the "Bot User OAuth Token" (starts with xoxb-)

Environment Variables

Set your Slack Bot Token as an environment variable:

export SLACK_BOT_TOKEN="xoxb-your-bot-token-here"

Or create a .env file in the project root:

SLACK_BOT_TOKEN=xoxb-your-bot-token-here

Usage

Running the Server

python slack_mcp_server.py

The server will start and listen for MCP connections via stdio.

Using with Claude Desktop

Add the following configuration to your Claude Desktop config file:

{
  "mcpServers": {
    "slack": {
      "command": "python",
      "args": ["/path/to/slack_mcp_server.py"],
      "env": {
        "SLACK_BOT_TOKEN": "xoxb-your-bot-token-here"
      }
    }
  }
}

Available Tools

The server provides the following tools:

Channel Operations

  • list_channels() - List all channels in the workspace
  • get_channel_info(channel_id) - Get detailed information about a channel
  • create_channel(name, is_private=False) - Create a new channel

Message Operations

  • send_message(channel, text, thread_ts=None) - Send a message to a channel
  • get_channel_history(channel, limit=10) - Get recent messages from a channel
  • search_messages(query, count=20) - Search for messages across the workspace

User Operations

  • get_user_info(user_id) - Get information about a user
  • list_users() - List all users in the workspace

File Operations

  • upload_file(channels, content, filename, title=None) - Upload a file to channels
  • search_files(query, count=20) - Search for files in the workspace

Reaction Operations

  • add_reaction(channel, timestamp, name) - Add an emoji reaction to a message
  • remove_reaction(channel, timestamp, name) - Remove an emoji reaction from a message

Examples

Sending a Message

# Through Claude Desktop or other MCP client
"Send a message to #general saying 'Hello from the MCP server!'"

Getting Channel History

# Get the last 5 messages from a channel
"Get the last 5 messages from the #development channel"

Searching Messages

# Search for messages containing specific keywords
"Search for messages containing 'deployment' in the last week"

Creating a Channel

# Create a new public channel
"Create a new channel called 'mcp-testing' for testing the MCP integration"

Error Handling

The server includes comprehensive error handling for:

  • Invalid Slack tokens
  • Rate limiting
  • Network connectivity issues
  • Invalid channel/user IDs
  • Permission errors

Security Considerations

  • Store your Slack Bot Token securely and never commit it to version control
  • Use environment variables or secure secret management
  • Regularly rotate your bot tokens
  • Monitor bot activity in your Slack workspace
  • Grant only the minimum required permissions

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For issues and questions:

  1. Check the Slack API documentation
  2. Review the MCP specification
  3. Open an issue in this repository

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured