- Create detailed setup guide with step-by-step instructions - Add troubleshooting section for common issues like cache sync errors - Include real terminal output example from successful integration - Add screenshot showing VS Code interface with Slack channel data - Remove excessive emojis for more professional documentation - Document retry logic improvements and CLI arguments
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Slack Integration Setup Guide
This guide provides step-by-step instructions for setting up Slack integration with LEANN.
Overview
LEANN's Slack integration uses MCP (Model Context Protocol) servers to fetch and index your Slack messages for RAG (Retrieval-Augmented Generation). This allows you to search through your Slack conversations using natural language queries.
Prerequisites
-
Slack Workspace Access: You need admin or owner permissions in your Slack workspace to create apps and configure OAuth tokens.
-
Slack MCP Server: Install a Slack MCP server (e.g.,
slack-mcp-servervia npm) -
LEANN: Ensure you have LEANN installed and working
Step 1: Create a Slack App
1.1 Go to Slack API Dashboard
- Visit https://api.slack.com/apps
- Click "Create New App"
- Choose "From scratch"
- Enter your app name (e.g., "LEANN Slack Integration")
- Select your workspace
- Click "Create App"
1.2 Configure App Permissions
Bot Token Scopes
- In your app dashboard, go to "OAuth & Permissions" in the left sidebar
- Scroll down to "Scopes" section
- Under "Bot Token Scopes", click "Add an OAuth Scope"
- Add the following scopes:
channels:read- Read public channel informationchannels:history- Read messages in public channelsgroups:read- Read private channel informationgroups:history- Read messages in private channelsim:read- Read direct message informationim:history- Read direct messagesmpim:read- Read group direct message informationmpim:history- Read group direct messagesusers:read- Read user informationteam:read- Read workspace information
App-Level Tokens (Optional)
Some MCP servers may require app-level tokens:
- Go to "Basic Information" in the left sidebar
- Scroll down to "App-Level Tokens"
- Click "Generate Token and Scopes"
- Enter a name (e.g., "LEANN Integration")
- Add the
connections:writescope - Click "Generate"
- Copy the token (starts with
xapp-)
1.3 Install App to Workspace
- Go to "OAuth & Permissions" in the left sidebar
- Click "Install to Workspace"
- Review the permissions and click "Allow"
- Copy the "Bot User OAuth Token" (starts with
xoxb-)
Step 2: Install Slack MCP Server
Option A: Using npm (Recommended)
# Install globally
npm install -g slack-mcp-server
# Or install locally
npm install slack-mcp-server
Option B: Using npx (No installation required)
# Use directly without installation
npx slack-mcp-server
Step 3: Configure Environment Variables
Create a .env file or set environment variables:
# Required: Bot User OAuth Token
SLACK_BOT_TOKEN=xoxb-your-bot-token-here
# Optional: App-Level Token (if your MCP server requires it)
SLACK_APP_TOKEN=xapp-your-app-token-here
# Optional: Workspace-specific settings
SLACK_WORKSPACE_ID=T1234567890 # Your workspace ID (optional)
Step 4: Test the Setup
4.1 Test MCP Server Connection
python -m apps.slack_rag \
--mcp-server "slack-mcp-server" \
--test-connection \
--workspace-name "Your Workspace Name"
This will test the connection and list available tools without indexing any data.
4.2 Index a Specific Channel
python -m apps.slack_rag \
--mcp-server "slack-mcp-server" \
--workspace-name "Your Workspace Name" \
--channels general \
--query "What did we discuss about the project?"
Success Example: Working Integration
Here's what a successful Slack integration looks like in practice:
Terminal Output
When you run the connection test, you should see output similar to this:
Testing Slack MCP Connection...
Environment: SLACK_MCP_XOXP_TOKEN = xoxb-16753592806-967...
Connected to Slack MCP server!
Authenticated with Slack.
Listing available MCP tools...
Found 5 available tools:
1. channels_list - Get list of channels
2. conversations_add_message - Add messages to channels
3. conversations_history - Get messages from channels
4. conversations_replies - Get thread messages
5. conversations_search_messages - Search messages with filters
Testing message fetch from 'random' channel...
Successfully fetched messages from channel random.
Visual Example
The following screenshot shows a successful integration with VS Code displaying the retrieved Slack channel data:
Key Success Indicators
- Authentication Success: Connected to your Slack workspace
- Tool Availability: 5 MCP tools ready for interaction
- Data Access: Retrieved channel directory with member counts and purposes
- Comprehensive Coverage: Access to multiple channels including specialized research groups
This demonstrates that your Slack integration is fully functional and ready for RAG queries across your entire workspace.
Common Issues and Solutions
Issue 1: "users cache is not ready yet" Error
Problem: You see this warning:
WARNING - Failed to fetch messages from channel random: Failed to fetch messages: {'code': -32603, 'message': 'users cache is not ready yet, sync process is still running... please wait'}
Solution: This is a common timing issue. The LEANN integration now includes automatic retry logic:
- Wait and Retry: The system will automatically retry with exponential backoff (2s, 4s, 8s, etc.)
- Increase Retry Parameters: If needed, you can customize retry behavior:
python -m apps.slack_rag \ --mcp-server "slack-mcp-server" \ --max-retries 10 \ --retry-delay 3.0 \ --channels general \ --query "Your query here" - Keep MCP Server Running: Start the MCP server separately and keep it running:
# Terminal 1: Start MCP server slack-mcp-server # Terminal 2: Run LEANN (it will connect to the running server) python -m apps.slack_rag --mcp-server "slack-mcp-server" --channels general --query "test"
Issue 2: "No message fetching tool found"
Problem: The MCP server doesn't have the expected tools.
Solution:
- Check if your MCP server is properly installed and configured
- Verify your Slack tokens are correct
- Try a different MCP server implementation
- Check the MCP server documentation for required configuration
Issue 3: Permission Denied Errors
Problem: You get permission errors when trying to access channels.
Solutions:
- Check Bot Permissions: Ensure your bot has been added to the channels you want to access
- Verify Token Scopes: Make sure you have all required scopes configured
- Channel Access: For private channels, the bot needs to be explicitly invited
- Workspace Permissions: Ensure your Slack app has the necessary workspace permissions
Issue 4: Empty Results
Problem: No messages are returned even though the channel has messages.
Solutions:
- Check Channel Names: Ensure channel names are correct (without the # symbol)
- Verify Bot Access: Make sure the bot can access the channels
- Check Date Ranges: Some MCP servers have limitations on message history
- Increase Message Limits: Try increasing the message limit:
python -m apps.slack_rag \ --mcp-server "slack-mcp-server" \ --channels general \ --max-messages-per-channel 1000 \ --query "test"
Advanced Configuration
Custom MCP Server Commands
If you need to pass additional parameters to your MCP server:
python -m apps.slack_rag \
--mcp-server "slack-mcp-server --token-file /path/to/tokens.json" \
--workspace-name "Your Workspace" \
--channels general \
--query "Your query"
Multiple Workspaces
To work with multiple Slack workspaces, you can:
- Create separate apps for each workspace
- Use different environment variables
- Run separate instances with different configurations
Performance Optimization
For better performance with large workspaces:
python -m apps.slack_rag \
--mcp-server "slack-mcp-server" \
--workspace-name "Your Workspace" \
--max-messages-per-channel 500 \
--no-concatenate-conversations \
--query "Your query"
Troubleshooting Checklist
- Slack app created with proper permissions
- Bot token (xoxb-) copied correctly
- App-level token (xapp-) created if needed
- MCP server installed and accessible
- Environment variables set correctly
- Bot invited to relevant channels
- Channel names specified without # symbol
- Sufficient retry attempts configured
- Network connectivity to Slack APIs
Getting Help
If you continue to have issues:
- Check Logs: Look for detailed error messages in the console output
- Test MCP Server: Use
--test-connectionto verify the MCP server is working - Verify Tokens: Double-check that your Slack tokens are valid and have the right scopes
- Community Support: Reach out to the LEANN community for help
Example Commands
Basic Usage
# Test connection
python -m apps.slack_rag --mcp-server "slack-mcp-server" --test-connection
# Index specific channels
python -m apps.slack_rag \
--mcp-server "slack-mcp-server" \
--workspace-name "My Company" \
--channels general random \
--query "What did we decide about the project timeline?"
Advanced Usage
# With custom retry settings
python -m apps.slack_rag \
--mcp-server "slack-mcp-server" \
--workspace-name "My Company" \
--channels general \
--max-retries 10 \
--retry-delay 5.0 \
--max-messages-per-channel 2000 \
--query "Show me all decisions made in the last month"
