🚀 Slack MCP Server

Transform your Slack workspace into an intelligent AI assistant with real-time responses

A production-ready Slack MCP Server that combines real-time Socket Mode integration with AI-powered tools. Built with FastMCP 2.8.0, this project provides 18+ tools for Claude Desktop and features an autonomous AI assistant that can plan and execute complex tasks.

⭐ What Makes This Special?

🤖 Real-Time Socket Mode Bot - Instant responses to Slack mentions (< 2 seconds)
🧠 Autonomous AI Agent - AI that plans its own execution strategies
🔧 18+ MCP Tools - Complete Slack workspace management via Claude Desktop
🌐 Web Research Integration - Real-time web search with Tavily API
⚡ Production Ready - Docker + AWS ECS deployment included
🛡️ Enterprise Security - AWS Secrets Manager integration

🎥 Demo

@MCP Bot analyze yesterday's #product-meeting and research mentioned technologies

↓ *2 seconds later* ↓

🤖 Analysis Complete! Found discussion about React 18, TypeScript 5.0, and Docker. 📊 Meeting Summary: [Detailed analysis...] 🔍 Technology Research: [Latest developments...] 📝 Action Items: [Extracted tasks...]

## 🚀 Quick Start (5 Minutes)

### 1. Clone & Install
```bash
git clone https://github.com/bahakizil/slack_mcp.git
cd slack_mcp
pip install -r requirements.txt

2. Configure API Keys

Create .env file:

SLACK_BOT_TOKEN=xoxb-your-bot-token        # From api.slack.com/apps
SLACK_APP_TOKEN=xapp-your-app-token        # For Socket Mode (required!)
OPENAI_API_KEY=sk-your-openai-key          # From platform.openai.com
TAVILY_API_KEY=tvly-your-tavily-key        # From tavily.com (optional)

3. Start the Server

python main.py

Success Output:

🤖 Starting Slack MCP Server with Real-time Mode
⚡ Socket Mode: Enabled (Real-time auto-responses)
✅ Bot ready for mentions: @MCP Bot
INFO: Uvicorn running on http://0.0.0.0:8003

4. Test in Slack

@MCP Bot hello!

🤖 Hello! I'm your AI assistant. How can I help you today? 😊

🎉 Your AI assistant is now live!

🔧 Complete Feature Set

📱 Slack Management (6 Tools)

Tool	Description	Example
send_slack_message	Send messages to channels	send_slack_message("general", "Hello team!")
get_slack_channels	List all workspace channels	get_slack_channels()
get_slack_messages	Retrieve channel history	get_slack_messages("engineering", limit=50)
search_slack_messages	Search across workspace	search_slack_messages("deployment")
create_slack_channel	Create new channels	create_slack_channel("new-project")
analyze_slack_conversation	AI-powered analysis	analyze_slack_conversation("planning", "summary")

🤖 AI Intelligence (3 Tools)

Tool	Description	Use Case
ask_ai	Ask questions to GPT-4o-mini	Technical explanations, brainstorming
autonomous_assistant	🌟 Self-planning AI agent	Complex multi-step tasks
Socket Mode Bot	Real-time auto-responses	Instant Slack interaction

🌐 Web Research (3 Tools)

Tool	Description	Example
search_web	General web search	search_web("latest AI developments 2024")
search_news	News-specific search	search_news("tech industry", days=7)
research_topic	Deep research analysis	research_topic("microservices architecture")

🔗 MCP Server Management (6 Tools)

Tool	Description	Purpose
add_mcp_server	Connect external MCP servers	Extend functionality
list_mcp_servers	Show all configured servers	Server management
connect_mcp_server	Establish connections	Activate external tools
disconnect_mcp_server	Close connections	Resource management
list_external_tools	Browse external tools	Tool discovery
call_external_tool	Execute external tools	Cross-server operations

🧠 Autonomous AI Assistant

The autonomous assistant is the crown jewel of this project. It can:

• 📋 Plan its own execution - No pre-programmed workflows
• 🔍 Discover tools dynamically - Adapts to available resources
• 🔄 Self-reflect and optimize - Learns from execution history
• 📊 Synthesize multi-source data - Combines Slack + web + AI knowledge

Example: Complex Task Execution

autonomous_assistant(
    request="Analyze all engineering discussions this week, research mentioned technologies, and create a strategic report",
    send_to_slack=True
)

What happens behind the scenes:

1. 🔍 Discovery: Finds available Slack channels and tools
2. 🧠 Planning: AI creates step-by-step execution plan
3. ⚡ Execution: Runs multiple tools in sequence
4. 🔬 Research: Web searches for mentioned technologies
5. 📊 Synthesis: Combines all data into comprehensive report
6. 📨 Delivery: Posts results to Slack automatically

🖥️ Claude Desktop Integration

Configuration

Add to claude_desktop_config.json:

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

{
  "mcpServers": {
    "slack-ai-assistant": {
      "command": "python",
      "args": ["/full/path/to/main.py"],
      "env": {
        "SLACK_BOT_TOKEN": "xoxb-your-actual-bot-token-here",
        "SLACK_APP_TOKEN": "xapp-your-actual-app-token-here", 
        "OPENAI_API_KEY": "sk-your-actual-openai-api-key-here",
        "TAVILY_API_KEY": "tvly-your-actual-tavily-api-key-here"
      }
    }
  }
}

Usage Examples in Claude Desktop

Meeting Analysis:

Analyze yesterday's #product-meeting channel and summarize key decisions, action items, and sentiment.

Tech Research + Slack Update:

Research current best practices for microservices deployment and share findings in #engineering channel.

Multi-Channel Intelligence:

Compare discussions across #design, #engineering, and #marketing channels this week. Identify common themes and potential collaboration opportunities.

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                   AUTONOMOUS AI SYSTEM                      │
├─────────────────────────────────────────────────────────────┤
│  ┌─────────────────┐    ┌─────────────────┐                │
│  │  SLACK MCP      │    │  TAVILY MCP     │                │
│  │  SERVER         │    │  SERVER         │                │
│  │  Port: 8001     │    │  Port: 8002     │                │
│  │                 │    │                 │                │
│  │ • Slack Tools   │    │ • Web Search    │                │
│  │ • AI Tools      │    │ • News Search   │                │
│  │ • Orchestration │    │ • Research      │                │
│  └─────────────────┘    └─────────────────┘                │
│           │                       │                        │
│           └───────────┐   ┌───────┘                        │
│                      │   │                               │
│               ┌─────────────────┐                          │
│               │ AUTONOMOUS      │                          │
│               │ AGENT           │                          │
│               │                 │                          │
│               │ • Tool Discovery│                          │
│               │ • Plan Creation │                          │
│               │ • Execution     │                          │
│               │ • Synthesis     │                          │
│               └─────────────────┘                          │
│                       │                                    │
│               ┌─────────────────┐                          │
│               │ OPENAI GPT      │                          │
│               │ (gpt-4.1-nano)  │                          │
│               └─────────────────┘                          │
└─────────────────────────────────────────────────────────────┘









## ☁️ Production Deployment

### 🐳 Docker Deployment
```bash
# Build and run locally
docker build -t slack-mcp-server .
docker run -p 8003:8003 --env-file .env slack-mcp-server

🚀 AWS ECS Deployment (Production)

# Automated deployment
./deploy.sh

Includes:

• ✅ Auto-scaling based on traffic
• ✅ Health checks and monitoring
• ✅ AWS Secrets Manager for secure credential management
• ✅ Application Load Balancer for high availability
• ✅ CloudWatch logging for debugging

📊 Production Features

• Zero downtime deployments
• Horizontal scaling (multiple instances)
• SSL/TLS termination
• Custom domain support
• Monitoring & alerting

🛡️ Security Best Practices

🔐 Credential Management

• Environment variables for local development
• AWS Secrets Manager for production
• No hardcoded secrets in code
• Git ignore for sensitive files

🛠️ Error Handling

• Graceful degradation when services are down
• Retry logic for transient failures
• User-friendly error messages
• Comprehensive logging

📈 Performance

• Socket Mode eliminates polling overhead
• Async processing for non-blocking operations
• Connection pooling for API efficiency
• Response time < 2 seconds

🎯 Real-World Use Cases

👥 For Teams

• Daily standups: "Summarize yesterday's progress across all channels"
• Sprint planning: "Analyze #product-backlog and prioritize by urgency"
• Knowledge sharing: "Research best practices for the technologies we discussed"

🏢 For Managers

• Team sentiment: "Analyze team mood and engagement this week"
• Progress tracking: "Extract action items from all project channels"
• Strategic insights: "Compare our technical discussions with industry trends"

🔬 For Developers

• Tech research: "Find the latest updates on frameworks we're using"
• Code review insights: "Analyze #code-review discussions for common issues"
• Learning automation: "Create weekly tech digest from our discussions"

📚 Documentation

• 📖 Quick Start Guide - 5-minute setup
• 🏗️ Complete Technical Guide - In-depth architecture
• 🚀 Deployment Guide - Production deployment
• ✅ Project Status - Current implementation status

🔧 Requirements

Slack App Setup

Required Bot Token Scopes:

channels:read, channels:history, chat:write, groups:read, 
groups:history, users:read, search:read, channels:manage

API Keys

• Slack Bot Token (xoxb-...) - Required
• Slack App Token (xapp-...) - Required for Socket Mode
• OpenAI API Key (sk-...) - Required for AI features
• Tavily API Key (tvly-...) - Optional for web search

System Requirements

• Python 3.11+
• 4GB RAM (minimum)
• Network access to Slack, OpenAI, and Tavily APIs

🔍 Troubleshooting

Common Issues

1. Socket Mode not working

# Check App Token configuration
echo $SLACK_APP_TOKEN  # Should start with xapp-

# Verify Socket Mode is enabled in Slack app settings
# Go to api.slack.com/apps → Your App → Socket Mode → Enable

2. Bot not responding

# Check bot token
echo $SLACK_BOT_TOKEN  # Should start with xoxb-

# Verify terminal shows:
# ✅ Socket Mode: Enabled (Real-time auto-responses)

3. Claude Desktop not loading

# Check config file path and restart Claude Desktop
# Verify Python is in PATH: python --version

Debug Mode

# Enable detailed logging
export DEBUG=true
export LOG_LEVEL=DEBUG
python main.py

🤝 Contributing

We welcome contributions! Here's how to get started:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

🎯 Areas for Contribution

• 🔧 New MCP tools - Extend functionality
• 🌐 Language support - Add more languages
• 📊 Analytics features - Advanced reporting
• 🔌 Integration templates - More external services
• 📚 Documentation - Examples and tutorials

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙋 Support & Community

• 💬 Issues: GitHub Issues
• 📖 Documentation: Check the docs/ folder
• 🐛 Bug Reports: Use issue templates
• 💡 Feature Requests: Community-driven roadmap

🌟 Acknowledgments

• FastMCP - Amazing MCP framework
• Slack SDK - Robust Slack integration
• OpenAI - Powerful AI capabilities
• Tavily - Excellent web search API

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🚀 Ready to Get Started?

1. ⭐ Star this repository if you find it useful
2. 🍴 Fork it to start customizing
3. 📥 Clone it and follow the 5-minute setup
4. 🤖 Mention your bot in Slack and watch the magic happen!

Built with ❤️ by Baha Kızıl

Transform your Slack workspace into an AI-powered productivity hub today! 🚀