Slack MCP Server

A Model Context Protocol (MCP) server that provides seamless integration with Slack's API. This server enables AI assistants like Claude to interact with Slack workspaces, manage channels, send messages, and perform various Slack operations.

Features

• Channel Management: List public channels and get channel information
• Message Operations: Post messages, reply to threads, and get message history
• User Management: List users and get detailed user profiles
• Reactions: Add emoji reactions to messages
• Thread Support: Get thread replies and post threaded responses
• Pagination: Support for paginated results across all list operations
• Authentication: Secure OAuth-based authentication via Nango

Prerequisites

• Python 3.13+
• Slack Bot Token with appropriate permissions
• Slack Team ID
• Nango integration for credential management (optional)

Installation

1. Clone the repository (or create the project structure):

mkdir slack-mcp-server
cd slack-mcp-server

2. Create a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

pip install -e .

Configuration

Environment Variables

Create a .env file in the project root with the following variables:

NANGO_BASE_URL=https://api.nango.dev
NANGO_SECRET_KEY=your-nango-secret-key
NANGO_CONNECTION_ID=your-connection-id
NANGO_INTEGRATION_ID=slack

Slack App Setup

1. Create a Slack App at api.slack.com
2. Add Bot Token Scopes:
   • channels:read - View basic information about public channels
   • channels:history - View messages in public channels
   • chat:write - Send messages as the bot
   • reactions:write - Add emoji reactions
   • users:read - View people in the workspace
   • users:read.email - View email addresses (if needed)
3. Install the app to your workspace
4. Copy the Bot User OAuth Token to your .env file

Claude Desktop Configuration

Add this configuration to your Claude Desktop config file:

Location:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "slack": {
      "command": "uvx",
      "args": ["git+https://github.com/ampcome-mcps/slack-mcp.git"],
      "env": {
        "NANGO_BASE_URL": "NANGO BASE URL",
        "NANGO_SECRET_KEY":"ENTER YOUR NANAGO SECRET KEY",
        "NANGO_CONNECTION_ID":"ENTER NANGO CONNECTION ID",
        "NANGO_INTEGRATION_ID":"ENTER NANGO INTEGRATION ID"
      }
    }
  }
}

Available Tools

The MCP server provides the following tools for Claude:

Channel Operations

• slack_list_channels - List public channels with pagination
• get_conversation_info - Get detailed information about a specific channel

Message Operations

• slack_post_message - Post a new message to a channel
• slack_reply_to_thread - Reply to a specific message thread
• slack_get_channel_history - Get recent messages from a channel
• slack_get_thread_replies - Get all replies in a message thread

User Operations

• slack_get_users - List all users in the workspace
• slack_get_user_profile - Get detailed profile information for a user

Interaction Operations

• slack_add_reaction - Add emoji reactions to messages

Usage Examples

Once configured with Claude, you can use natural language commands like:

• "List all the channels in our Slack workspace"
• "Post a message to the #general channel saying 'Hello team!'"
• "Get the recent messages from the #development channel"
• "Reply to that thread with 'Thanks for the update'"
• "Add a thumbs up reaction to that message"
• "Show me the user profile for John Doe"

Running the Server Standalone

For testing or development purposes, you can run the server directly:

python main.py

The server will start and listen for MCP protocol messages via stdin/stdout.

Project Structure

slack-mcp-server/
├── main.py              # Main MCP server implementation
├── pyproject.toml       # Project configuration and dependencies  
├── .env                 # Environment variables (create from template)
├── .env.example         # Environment variables template
├── README.md           # This file
└── .gitignore          # Git ignore rules

Development

Key Components

• SlackClient: Handles all Slack API interactions using httpx
• MCP Server: Implements the Model Context Protocol for tool exposure
• Tool Definitions: Structured schemas for all available Slack operations
• Error Handling: Comprehensive error handling and logging

Adding New Tools

To add new Slack API functionality:

1. Add the method to the SlackClient class
2. Define the tool schema in the TOOLS list
3. Add the tool handler in the call_tool function

Dependencies

• httpx - Async HTTP client for Slack API calls
• mcp - Model Context Protocol framework
• python-dotenv - Environment variable management

Troubleshooting

Common Issues

1. Authentication Errors: Verify your SLACK_BOT_TOKEN is correct and has necessary scopes
2. Channel Not Found: Ensure the bot has access to the channel and it's not archived
3. Permission Denied: Check that your Slack app has the required OAuth scopes
4. Rate Limiting: The server handles Slack's rate limits automatically

Debugging

The server logs debug information to stderr. Check the Claude Desktop logs or run the server directly to see detailed error messages.

Security Notes

• Store sensitive tokens in environment variables, never in code
• Use .gitignore to prevent committing .env files
• Regularly rotate your Slack bot tokens
• Follow the principle of least privilege for OAuth scopes

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Submit a pull request

License

MIT License - see LICENSE file for details.

Support

For issues related to:

• Slack API: Check the Slack API documentation
• MCP Protocol: See the MCP specification
• This server: Open an issue in the project repository