Slack MCP Server

What does “Slack” MCP Server do?

The Slack MCP Server is a Model Context Protocol (MCP) server designed to seamlessly connect AI assistants with Slack Workspaces. It enables advanced workflow automation by allowing AI agents to interact directly with Slack through both Stdio and Server-Sent Events (SSE) transports. With built-in proxy support, the server operates without requiring any bots or permissions from workspace administrators, making it easy to deploy in a wide variety of environments—including direct messages (DMs) and group DMs. By bridging AI assistants and Slack, the Slack MCP Server empowers developers to automate messaging tasks, manage conversations, and integrate external data or services into Slack, thereby enhancing productivity and streamlining development workflows.

List of Prompts

No prompt templates are mentioned in the repository.

List of Resources

No explicit MCP resources are listed in the available repository documentation.

List of Tools

No tool definitions or tool lists are found in the repository files or documentation.

Use Cases of this MCP Server

• Automated Slack Messaging: Enables AI agents to send messages, notifications, or alerts to Slack channels, DMs, or group DMs, enhancing team communication and response times.
• Workflow Integration: Allows developers to integrate Slack with external APIs or databases via MCP, automating data retrieval and reporting directly within Slack conversations.
• No-Admin Deployment: Facilitates secure, permissionless integration into Slack workspaces without the need for admin approval or bot installation, ideal for organizations with strict IT policies.
• Multi-Transport Support: Offers flexibility for different deployment environments by supporting both Stdio and SSE transports for Slack interactions.
• Proxy Compatibility: Ensures that organizations operating behind strict network proxies can still leverage AI-powered Slack integrations.

How to set it up

Windsurf

1. Ensure prerequisites are installed (e.g., Node.js, MCP-compatible client).
2. Locate the configuration file for MCP servers in Windsurf.
3. Add the Slack MCP Server using the appropriate JSON snippet.
4. Save the configuration and restart Windsurf.
5. Verify the Slack MCP Server is connected.

"mcpServers": {
  "slack-mcp": {
    "command": "npx",
    "args": ["@slack/mcp-server@latest"]
  }
}

Claude

1. Install required dependencies (Node.js, Claude client).
2. Open Claude’s configuration file.
3. Insert the Slack MCP Server details in the mcpServers section.
4. Restart Claude.
5. Confirm the connection to Slack MCP Server.

"mcpServers": {
  "slack-mcp": {
    "command": "npx",
    "args": ["@slack/mcp-server@latest"]
  }
}

Cursor

1. Make sure Node.js and Cursor are installed.
2. Edit the Cursor configuration file.
3. Add Slack MCP Server under the mcpServers object.
4. Save changes and restart Cursor.
5. Check if Slack integration is active.

"mcpServers": {
  "slack-mcp": {
    "command": "npx",
    "args": ["@slack/mcp-server@latest"]
  }
}

Cline

1. Install all necessary prerequisites (Node.js, Cline client).
2. Navigate to Cline’s MCP server configuration file.
3. Add the Slack MCP Server configuration.
4. Save and restart Cline.
5. Validate setup by testing Slack connectivity.

"mcpServers": {
  "slack-mcp": {
    "command": "npx",
    "args": ["@slack/mcp-server@latest"]
  }
}

Securing API Keys

To secure API keys, use environment variables. In your configuration, specify env and inputs as shown below:

"mcpServers": {
  "slack-mcp": {
    "command": "npx",
    "args": ["@slack/mcp-server@latest"],
    "env": {
      "SLACK_TOKEN": "${SLACK_TOKEN}"
    },
    "inputs": {
      "slackToken": "${SLACK_TOKEN}"
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "slack-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “slack-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

The Slack MCP Server provides a streamlined way to connect AI with Slack, with good setup documentation and security practices. However, it lacks explicit documentation of MCP-specific prompts, resources, and tools, which limits its completeness for advanced users.

MCP rating: 4/10

MCP Score