sooperset/mcp-client-slackbot

A simple Slack bot that uses the Model Context Protocol (MCP) to enhance its capabilities with external tools.
## Features
AI-Powered Assistant: Responds to messages in channels and DMs using LLM capabilities
MCP Integration: Full access to MCP tools like SQLite database and web fetching
Multi-LLM Support: Works with OpenAI, Groq, and Anthropic models
App Home Tab: Shows available tools and usage information
## Setup
### 1. Create a Slack App
1. Go to api.slack.com/apps and click "Create New App"
2. Choose "From an app manifest" and select your workspace
3. Copy the contents of mcp_simple_slackbot/manifest.yaml into the manifest editor
4. Create the app and install it to your workspace
5. Under the "Basic Information" section, scroll down to "App-Level Tokens"
6. Click "Generate Token and Scopes" and:
Enter a name like "mcp-assistant"
Add the connections:write scope
Click "Generate"
7. Take note of both your:
Bot Token (xoxb-...) found in "OAuth & Permissions"
App Token (xapp-...) that you just generated
### 2. Install Dependencies
bash
# Create a virtual environment
python -m venv venv
# Activate the virtual environment
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install project dependencies
pip install -r mcp_simple_slackbot/requirements.txt
### 3. Configure Environment Variables
Create a .env file in the mcp_simple_slackbot directory (see .env.example for a template):
# Slack API credentials
SLACK_BOT_TOKEN=xoxb-your-token
SLACK_APP_TOKEN=xapp-your-token
# LLM API credentials
OPENAI_API_KEY=sk-your-openai-key
# or use GROQ_API_KEY or ANTHROPIC_API_KEY
# LLM configuration
LLM_MODEL=gpt-4-turbo
## Running the Bot
bash
# Navigate to the module directory
cd mcp_simple_slackbot
# Run the bot directly
python main.py
The bot will:
1. Connect to all configured MCP servers
2. Discover available tools
3. Start the Slack app in Socket Mode
4. Listen for mentions and direct messages
## Usage
Direct Messages: Send a direct message to the bot
Channel Mentions: Mention the bot in a channel with @MCP Assistant
App Home: Visit the bot's App Home tab to see available tools
## Architecture
The bot is designed with a focused architecture:
1. SlackMCPBot: Core class managing Slack events and message processing
2. LLMClient: Handles communication with LLM APIs (OpenAI, Groq, Anthropic)