Slack Feedback MCP Server

MCP server for collecting product feedback from Bryan and others in the StartupOS Slack workspace.

What It Does

This MCP server provides three tools for Claude Code:

1. get_stakeholder_feedback - Pull messages from Bryan (and others) with flexible date filtering
2. get_thread_context - Retrieve full conversation threads
3. search_feedback - Search feedback by keywords

Setup Instructions

Step 1: Create the Slack Channel

1. In your StartupOS Slack workspace, create a new channel: #bryan-product-feedback
2. Invite Bryan to the channel
3. Get the channel ID:
   • Right-click the channel name
   • Select "View channel details"
   • Scroll to the bottom and copy the Channel ID (starts with C...)

Step 2: Get Bryan's User ID

1. Click on Bryan's profile in Slack
2. Click "More" → "Copy member ID"
3. Save this ID (starts with U...)

Step 3: Create the Slack App

1. Go to https://api.slack.com/apps
2. Click "Create New App" → "From scratch"
3. Name: "Feedback Collector MCP"
4. Workspace: StartupOS
5. Click "Create App"

Step 4: Configure Bot Permissions

1. In your app settings, go to "OAuth & Permissions"
2. Scroll to "Scopes" → "Bot Token Scopes"
3. Add these scopes:
   • channels:history - Read messages in public channels
   • channels:read - View basic channel info
   • groups:history - Read messages in private channels
   • groups:read - View basic private channel info
   • users:read - Get user info
   • search:read - Search messages

Step 5: Install to Workspace

1. Scroll to the top of "OAuth & Permissions"
2. Click "Install to Workspace"
3. Click "Allow"
4. Copy the "Bot User OAuth Token" (starts with xoxb-)

Step 6: Add Bot to Channel

1. Go to the #bryan-product-feedback channel in Slack
2. Type: /invite @Feedback Collector MCP
3. Press Enter

Step 7: Deploy to Railway

Option A: Deploy from GitHub (Recommended)

1. Push this code to a GitHub repository
2. Go to https://railway.app and sign up with GitHub
3. Click "New Project" → "Deploy from GitHub repo"
4. Select your repository
5. Railway will auto-detect the Node.js project

Option B: Deploy via CLI

npm install -g @railway/cli
railway login
railway init
railway up

Step 8: Set Environment Variables in Railway

In your Railway project dashboard:

1. Go to the "Variables" tab

2. Add these variables:

   • SLACK_BOT_TOKEN = your xoxb- token from Step 5
   • SLACK_BRYAN_USER_ID = Bryan's user ID from Step 2
   • FEEDBACK_CHANNEL_ID = channel ID from Step 1
   • PORT = 3000

3. Save and redeploy if needed

Step 9: Get Your Railway URL

After deployment, Railway assigns you a public URL like:

https://slack-feedback-mcp-production-xxxx.up.railway.app

Copy this URL.

Step 10: Configure Claude Code

Add to your Claude Code MCP settings file:

Location: ~/.claude/settings.json or project .mcp.json

{
  "mcpServers": {
    "slack-feedback": {
      "type": "sse",
      "url": "https://YOUR-RAILWAY-URL.up.railway.app/sse"
    }
  }
}

Replace YOUR-RAILWAY-URL with your actual Railway URL.

Testing

Restart Claude Code and try:

• "Pull feedback from Bryan from the last 48 hours"
• "Search for feedback mentioning 'authentication'"
• "Get the full thread for this message" (when you have a thread_ts)

Available Tools

get_stakeholder_feedback

Pull messages from the feedback channel with date filtering.

Parameters:

• time_range (optional): "last 48 hours", "last 7 days", "today", "this week", etc.
• stakeholder (optional): "bryan" or "all" (default: "all")
• channel_id (optional): Specific channel to search

Example:

Pull Bryan's feedback from the last 2 days

get_thread_context

Get full conversation thread including all replies.

Parameters:

• channel_id (required): Channel ID
• thread_ts (required): Parent message timestamp

Example:

Get the full thread for message ts: 1234567890.123456 in channel C0XXXXXXXXX

search_feedback

Search Bryan's messages by keyword.

Parameters:

• query (required): Search keywords
• time_range (optional): Time range filter

Example:

Search Bryan's feedback for "login flow" from the last month

Local Development

1. Copy .env.example to .env
2. Fill in your values
3. Run:

npm run dev

Server runs on http://localhost:3000

Security Notes

• Never commit .env or tokens to git
• Slack bot token only has read permissions
• Railway environment variables are encrypted at rest

Troubleshooting

"Channel not found" error:

• Make sure you invited the bot to the channel (/invite @Feedback Collector MCP)
• Verify the channel ID is correct

"Not authorized" error:

• Check that all required scopes are added in the Slack app settings
• Reinstall the app to workspace after adding scopes

No messages returned:

• Verify Bryan's user ID is correct
• Check that there are actually messages in the time range
• Try a longer time range like "last 30 days"

Future Enhancements

The codebase is structured to support Claude-powered summarization and categorization of feedback. To enable this:

1. Add ANTHROPIC_API_KEY environment variable
2. Uncomment summarization logic in the tools
3. Add @anthropic-ai/sdk dependency

For now, raw messages are returned for maximum flexibility.