# 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 1. **Slack Workspace Access**: You need admin or owner permissions in your Slack workspace to create apps and configure OAuth tokens. 2. **Slack MCP Server**: Install a Slack MCP server (e.g., `slack-mcp-server` via npm) 3. **LEANN**: Ensure you have LEANN installed and working ## Step 1: Create a Slack App ### 1.1 Go to Slack API Dashboard 1. Visit [https://api.slack.com/apps](https://api.slack.com/apps) 2. Click **"Create New App"** 3. Choose **"From scratch"** 4. Enter your app name (e.g., "LEANN Slack Integration") 5. Select your workspace 6. Click **"Create App"** ### 1.2 Configure App Permissions #### Bot Token Scopes 1. In your app dashboard, go to **"OAuth & Permissions"** in the left sidebar 2. Scroll down to **"Scopes"** section 3. Under **"Bot Token Scopes"**, click **"Add an OAuth Scope"** 4. Add the following scopes: - `channels:read` - Read public channel information - `channels:history` - Read messages in public channels - `groups:read` - Read private channel information - `groups:history` - Read messages in private channels - `im:read` - Read direct message information - `im:history` - Read direct messages - `mpim:read` - Read group direct message information - `mpim:history` - Read group direct messages - `users:read` - Read user information - `team:read` - Read workspace information #### App-Level Tokens (Optional) Some MCP servers may require app-level tokens: 1. Go to **"Basic Information"** in the left sidebar 2. Scroll down to **"App-Level Tokens"** 3. Click **"Generate Token and Scopes"** 4. Enter a name (e.g., "LEANN Integration") 5. Add the `connections:write` scope 6. Click **"Generate"** 7. Copy the token (starts with `xapp-`) ### 1.3 Install App to Workspace 1. Go to **"OAuth & Permissions"** in the left sidebar 2. Click **"Install to Workspace"** 3. Review the permissions and click **"Allow"** 4. Copy the **"Bot User OAuth Token"** (starts with `xoxb-`) ## Step 2: Install Slack MCP Server ### Option A: Using npm (Recommended) ```bash # Install globally npm install -g slack-mcp-server # Or install locally npm install slack-mcp-server ``` ### Option B: Using npx (No installation required) ```bash # Use directly without installation npx slack-mcp-server ``` ## Step 3: Configure Environment Variables Create a `.env` file or set environment variables: ```bash # 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 ```bash 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 ```bash 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?" ``` ### 4.3 Real RAG Query Example This example demonstrates a successful Slack RAG integration query against the Sky Lab Computing workspace's "random" channel. The system successfully retrieves actual conversation messages and performs semantic search with high relevance scores. **Key Features Demonstrated:** - ✅ **Real Slack Integration**: Successfully connects to Slack via MCP server - ✅ **Actual Message Retrieval**: Fetches real conversation history, not just metadata - ✅ **Working RAG Pipeline**: Complete index building, search, and response generation - ✅ **High Relevance Search**: Score of 0.5673 for research papers query - ✅ **Rich Content**: Real research discussions about AI papers, lab updates, etc. ### Screenshots ![Sky Random RAG - Real Slack Integration](videos/slack_integration.png) ![Sky Random RAG - Additional Demo](videos/slack_integration_2.png) ### Prerequisites - Bot is installed in the Sky Lab Computing workspace and invited to the target channel (run `/invite @YourBotName` in the channel if needed) - Bot token available and exported in the same terminal session ### Commands 1) Set the workspace token for this shell ```bash export SLACK_MCP_XOXP_TOKEN="xoxb-***-redacted-***" ``` 2) Run a real query against the “random” channel by channel ID (C0GN5BX0F) ```bash python test_channel_by_id_or_name.py \ --channel-id C0GN5BX0F \ --workspace-name "Sky Lab Computing" \ --query "PUBPOL 290" ``` Expected: The output contains a matching message (e.g., “do we have a channel for class PUBPOL 290 this semester?”) followed by a compact RAG-style answer section. 3) Optional: Ask a broader question ```bash python test_channel_by_id_or_name.py \ --channel-id C0GN5BX0F \ --workspace-name "Sky Lab Computing" \ --query "What is LEANN about?" ``` Notes: - If you see `not_in_channel`, invite the bot to the channel and re-run. - If you see `channel_not_found`, confirm the channel ID and workspace. - Deep search via server-side “search” tools may require additional Slack scopes; the example above performs client-side filtering over retrieved history. ## 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: 1. **Wait and Retry**: The system will automatically retry with exponential backoff (2s, 4s, 8s, etc.) 2. **Increase Retry Parameters**: If needed, you can customize retry behavior: ```bash python -m apps.slack_rag \ --mcp-server "slack-mcp-server" \ --max-retries 10 \ --retry-delay 3.0 \ --channels general \ --query "Your query here" ``` 3. **Keep MCP Server Running**: Start the MCP server separately and keep it running: ```bash # 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**: 1. Check if your MCP server is properly installed and configured 2. Verify your Slack tokens are correct 3. Try a different MCP server implementation 4. Check the MCP server documentation for required configuration ### Issue 3: Permission Denied Errors **Problem**: You get permission errors when trying to access channels. **Solutions**: 1. **Check Bot Permissions**: Ensure your bot has been added to the channels you want to access 2. **Verify Token Scopes**: Make sure you have all required scopes configured 3. **Channel Access**: For private channels, the bot needs to be explicitly invited 4. **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**: 1. **Check Channel Names**: Ensure channel names are correct (without the # symbol) 2. **Verify Bot Access**: Make sure the bot can access the channels 3. **Check Date Ranges**: Some MCP servers have limitations on message history 4. **Increase Message Limits**: Try increasing the message limit: ```bash 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: ```bash 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: 1. Create separate apps for each workspace 2. Use different environment variables 3. Run separate instances with different configurations ### Performance Optimization For better performance with large workspaces: ```bash 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: 1. **Check Logs**: Look for detailed error messages in the console output 2. **Test MCP Server**: Use `--test-connection` to verify the MCP server is working 3. **Verify Tokens**: Double-check that your Slack tokens are valid and have the right scopes 4. **Community Support**: Reach out to the LEANN community for help ## Example Commands ### Basic Usage ```bash # 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 ```bash # 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" ```