slack-mcp-server

The slack-mcp-server is an MCP (Model Context Protocol) server designed for accessing the Slack API. This server enables AI assistants to interact with the Slack API through a standardized interface. Implemented primarily in JavaScript, it supports both local and remote client communications. This allows for various operations within Slack, such as sending messages, listing channels, and replying to threads.

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README
slack-mcp-server

A MCP(Model Context Protocol) server for accessing Slack API. This server allows AI assistants to interact with the Slack API through a standardized interface.

Transport Support

This server supports both traditional and modern MCP transport methods:

  • Stdio Transport (default): Process-based communication for local integration
  • Streamable HTTP Transport: HTTP-based communication for web applications and remote clients
Features

Available tools:

  • slack_list_channels - List public channels in the workspace with pagination
  • slack_post_message - Post a new message to a Slack channel
  • slack_reply_to_thread - Reply to a specific message thread in Slack
  • slack_add_reaction - Add a reaction emoji to a message
  • slack_get_channel_history - Get recent messages from a channel
  • slack_get_thread_replies - Get all replies in a message thread
  • slack_get_users - Retrieve basic profile information of all users in the workspace
  • slack_get_user_profiles - Get multiple users' profile information in bulk (efficient for batch operations)
  • slack_search_messages - Search for messages in the workspace with powerful filters:
    • Basic query search
    • Location filters: in_channel
    • User filters: from_user, with
    • Date filters: before (YYYY-MM-DD), after (YYYY-MM-DD), on (YYYY-MM-DD), during (e.g., "July", "2023")
    • Content filters: has (emoji reactions), is (saved/thread)
    • Sorting options by relevance score or timestamp
Quick Start
Installation
npm install @ubie-oss/slack-mcp-server

NOTE: Its now hosted in GitHub Registry so you need your PAT.

Configuration

You need to set the following environment variables:

  • SLACK_BOT_TOKEN: Slack Bot User OAuth Token
  • SLACK_USER_TOKEN: Slack User OAuth Token (required for some features like message search)

You can also create a .env file to set these environment variables:

SLACK_BOT_TOKEN=xoxb-your-bot-token
SLACK_USER_TOKEN=xoxp-your-user-token
Usage
Start the MCP server

Stdio Transport (default):

npx @ubie-oss/slack-mcp-server

Streamable HTTP Transport:

npx @ubie-oss/slack-mcp-server -port 3000

You can also run the installed module with node:

# Stdio transport
node node_modules/.bin/slack-mcp-server

# HTTP transport  
node node_modules/.bin/slack-mcp-server -port 3000

Command Line Options:

  • -port <number>: Start with Streamable HTTP transport on specified port
  • -h, --help: Show help message
Client Configuration

For Stdio Transport (Claude Desktop, etc.):

{
  "slack": {
    "command": "npx",
    "args": [
      "-y",
      "@ubie-oss/slack-mcp-server"
    ],
    "env": {
      "NPM_CONFIG_//npm.pkg.github.com/:_authToken": "<your-github-pat>",
      "SLACK_BOT_TOKEN": "<your-bot-token>",
      "SLACK_USER_TOKEN": "<your-user-token>"
    }
  }
}

For Streamable HTTP Transport (Web applications):

Start the server:

SLACK_BOT_TOKEN=<your-bot-token> SLACK_USER_TOKEN=<your-user-token> npx @ubie-oss/slack-mcp-server -port 3000

Connect to: http://localhost:3000/mcp

See examples/README.md for detailed client examples.

Implementation Pattern

This server adopts the following implementation pattern:

  1. Define request/response using Zod schemas

    • Request schema: Define input parameters
    • Response schema: Define responses limited to necessary fields
  2. Implementation flow:

    • Validate request with Zod schema
    • Call Slack WebAPI
    • Parse response with Zod schema to limit to necessary fields
    • Return as JSON

For example, the slack_list_channels implementation parses the request with ListChannelsRequestSchema, calls slackClient.conversations.list, and returns the response parsed with ListChannelsResponseSchema.

Development
Available Scripts
  • npm run dev - Start the server in development mode with hot reloading
  • npm run build - Build the project for production
  • npm run start - Start the production server
  • npm run lint - Run linting checks (ESLint and Prettier)
  • npm run fix - Automatically fix linting issues
Contributing
  1. Fork the repository
  2. Create your feature branch
  3. Run tests and linting: npm run lint
  4. Commit your changes
  5. Push to the branch
  6. Create a Pull Request
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