About slack-mcp-server
slack-mcp-server is an MCP server that gives AI assistants access to the Slack API through a standardized interface. It supports both Stdio and Streamable HTTP transports, so it works for local integrations and remote clients.
Key features
- 01Channel and message reading tools
- 02Message posting and thread replies
- 03Emoji reaction support
- 04Bulk user profile lookup
- 05Message search with multiple filters
- 06Optional safe search mode
Use cases
- 01Summarizing recent channel messages with an AI assistant
- 02Replying in threads or adding reactions through an assistant
- 03Searching message history by user, date or channel
MCP support
This project is an MCP server that exposes Slack operations such as slack_list_channels, slack_post_message and slack_search_messages as tools to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEslack-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 paginationslack_post_message- Post a new message to a Slack channelslack_reply_to_thread- Reply to a specific message thread in Slackslack_add_reaction- Add a reaction emoji to a messageslack_get_channel_history- Get recent messages from a channelslack_get_thread_replies- Get all replies in a message threadslack_get_users- Retrieve basic profile information of all users in the workspaceslack_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 TokenSLACK_USER_TOKEN: Slack User OAuth Token (required for some features like message search)SLACK_SAFE_SEARCH(optional): When set totrue, automatically excludes private channels, DMs, and group DMs from search results. This is enforced server-side and cannot be overridden by clients.
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
SLACK_SAFE_SEARCH=true # Optional: Enable safe search mode
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>",
"SLACK_SAFE_SEARCH": "true"
}
}
}
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:
-
Define request/response using Zod schemas
- Request schema: Define input parameters
- Response schema: Define responses limited to necessary fields
-
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 reloadingnpm run build- Build the project for productionnpm run start- Start the production servernpm run lint- Run linting checks (ESLint and Prettier)npm run fix- Automatically fix linting issues
Contributing
- Fork the repository
- Create your feature branch
- Run tests and linting:
npm run lint - Commit your changes
- Push to the branch
- Create a Pull Request
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.