Automate Discord Spam Detection & Moderation with AI and n8n

1. Opening Problem Statement

Meet Sarah, a community manager for a fast-growing Discord server with thousands of active members. Every day, she faces the tedious task of manually scanning countless messages to identify and deal with spam — messages promoting products, scams, or unsolicited links that disrupt conversations and annoy genuine members. This manual process eats up hours of her day, leading to delays, errors, and inconsistent moderation actions. Sometimes spam slips through unnoticed, damaging community trust and engagement. Sarah needs a reliable, automated way to detect spam messages and involve moderators only when necessary.

2. What This Automation Does

When Sarah activates this n8n workflow, here’s what happens automatically:

• Fetches recent messages from a predefined Discord channel at scheduled intervals using a Discord bot.
• Removes duplicates to avoid processing the same message multiple times.
• Groups messages by individual users, minimizing notification noise and batch-processing messages for each user.
• Uses AI-powered text classification via the Langchain Text Classifier node to detect which messages are spam versus not spam.
• Notifies human moderators through Discord with a custom dropdown form to decide appropriate action—delete, warn, or ignore.
• Executes moderation actions automatically based on moderator choices, including deleting messages and warning users privately.

This workflow saves Sarah and her team countless hours each week by automating spam identification and ensuring swift, consistent moderation with human oversight.

3. Prerequisites ⚙️

• n8n account (cloud or self-hosted). Consider self-hosting options for uptime and control (see Hostinger self-hosting guide).
• Discord Bot account with permissions to read messages, send messages, delete messages, and message users in the target Discord server.
• OpenAI API key for AI text classification using the Langchain Text Classifier and OpenAI Chat model.

4. Step-by-Step Guide

Step 1: Setting Up the Schedule Trigger

In n8n, click + New Node → search for and select Schedule Trigger. Configure it to run every hour (or your preferred interval) to check for new messages automatically. Expect the workflow to start periodically without manual input.

Common mistake: Setting the trigger interval too long may cause spam to remain undetected for hours.

Step 2: Get Recent Messages from Discord Channel

Click + New Node → choose Discord → select “Get All Messages” operation. Enter your Discord guildId (server ID) and the channelId for the channel you want to monitor (e.g., general chat). Link your Discord Bot API credentials here.

Result: The node fetches all latest messages from the designated channel.

Tip: If your server is very active, consider adjusting fetch limits or trigger intervals.

Step 3: Remove Duplicate Messages

Add a Remove Duplicates node next. Configure it to track message id with history size 100 to avoid processing same messages repeatedly. This ensures efficiency and accuracy.

Step 4: Group Messages By User

Add a Code node with JavaScript to group fetched messages based on user ID. Copy-paste this code:

const groupByUser = {};

for (const item of $input.all()) {
  if (!groupByUser[item.json.author.id]) {
    groupByUser[item.json.author.id] = [];
  }
  groupByUser[item.json.author.id].push(item.json);
}

return { json : { groupByUser } };

This grouping minimizes notification spam to moderators by processing each user’s messages in batches.

Step 5: Split and Batch Processing of Users

Use Split Out node on the grouped data, then a Split In Batches node to loop through each user batch sequentially. This sets the stage for individual spam analysis per user.

Step 6: Analyze Messages Using AI Spam Detection

Connect to the Langchain Text Classifier node configured with two categories: is_spam and is_not_spam. Feed it the concatenated messages content to AI for classification.

Tip: This AI model uses OpenAI GPT-based analysis via the Langchain LMChat OpenAI node configured with your OpenAI API key and model “o3-mini”.

Step 7: Flag Messages Based on Classification

Depending on AI results, use two Set nodes to mark messages flagged as spam (is_spam: true) or not (is_spam: false), then merge results.

Step 8: Filter Only Spam Messages

Add a Filter node to pass only messages where is_spam is true, directing further review by moderators.

Step 9: Check If There Are Flagged Messages

Use an If node to determine if any flagged spam messages exist to proceed only when needed.

Step 10: Use Subworkflow to Manage Moderation per User

Add Execute Workflow node as a subworkflow trigger to handle moderation concurrently without blocking others.

Step 11: Notify Moderators with Human-In-The-Loop

In the subworkflow, use Discord node with “Send and Wait” operation to notify moderators with details about flagged messages. Attach a custom form dropdown letting moderators choose from:

• Delete Message and Warn User
• Do nothing and Warn User
• Do nothing

This approach balances automation with human judgment to avoid false positives.

Step 12: Receive Moderator Instructions

Use a Switch node to handle the moderator’s chosen action and trigger appropriate next steps.

Step 13: Delete Messages and Warn User

If deletion is selected, a Code node extracts message IDs, and a Discord node deletes the flagged messages and sends a private warning message to the user.

Step 14: Warn User Only

If “Warn User Only” is selected, the bot sends a private friendly warning without deleting messages.

Step 15: No Action Taken

If “Do Nothing” is selected, the workflow terminates politely without further action.

5. Customizations ✏️

• Expand Spam Categories: In the Spam Detection node, add more categories like “phishing”, “offensive language”, or “links” to refine classification.
• Adjust Scheduling Frequency: Change the Schedule Trigger interval to match your community’s activity level.
• Add More Moderator Actions: In the Notify Moderators with Send & Wait node, update the dropdown to include actions like “Mute User” or “Temporary Ban”.
• Customize Warning Messages: Edit the content in the Warn User and Warn User Only Discord nodes to fit your community’s tone.
• Increase Duplicate History Size: In the Only Once node, increase historySize if your server has very high message volume.

6. Troubleshooting 🔧

Problem: “No messages retrieved from Discord node.”
Cause: Incorrect guildId or channelId, or missing bot permissions.
Solution: Verify server and channel IDs are correct and the bot has message reading permissions.

Problem: “AI node returns unexpected category or error.”
Cause: Misconfiguration of the Langchain Text Classifier or OpenAI API key issues.
Solution: Double-check API credentials in OpenAI and Langchain nodes and ensure category definitions match expected inputs.

Problem: “Moderator form not appearing or no response recorded.”
Cause: Discord bot token lacking “Send and Wait” permissions or workflow misconfiguration.
Solution: Confirm Discord bot permissions and test notifications independently to ensure forms are delivered correctly.

7. Pre-Production Checklist ✅

• Confirm your Discord bot API credentials are valid and have required permissions (read/delete/send messages, message users).
• Verify OpenAI account and API key authorization for the Langchain nodes.
• Test scheduled trigger to confirm messages are fetched and duplicates removed as expected.
• Run sample message through AI text classifier to check spam detection accuracy.
• Test moderator notifications and ensure the dropdown form submits responses properly.
• Backup your workflow before major tweak or deployment.

8. Deployment Guide

Once you verify all nodes execute correctly, activate the workflow in n8n. Let it run on the scheduled interval. Monitor logs occasionally to ensure messages are processed effectively and moderation actions are executed as expected.

Adjust scheduling and AI parameters based on observed workload and spam trends. Use the human-in-the-loop feature to maintain quality control while automating routine work.

9. FAQs

Q: Can I use a different AI model for spam detection?
A: Yes, you can replace the Langchain Text Classifier with any AI model compatible with n8n, but OpenAI works smoothly for this use case.

Q: Does running this workflow consume my OpenAI credits?
A: Yes, each classification query uses OpenAI API credits—monitor usage accordingly.

Q: Is user data safe?
A: Yes, this workflow processes data within your environment and Discord’s API securely. Always follow secure credential management.

Q: Will this scale to large Discord servers?
A: The batch processing and subworkflow parallelization are designed to handle large volumes efficiently.

10. Conclusion

By implementing this n8n workflow, Sarah automated her Discord server’s spam moderation, reducing hours spent on manual review and enabling consistent enforcement of community rules. The AI-powered classification combined with human-in-the-loop moderation ensures balanced, reliable decision-making—saving time and improving member experience.

Next, consider expanding to detect other message types like offensive language, automate welcoming new members, or integrate with other community platforms for central moderation.

You’re now ready to deploy your own smart, responsive Discord spam detection system using n8n and AI!