MCP Tools
Slack Slack
Claude Claude

Monitor customer sentiment in real time

Detect sentiment shifts across support channels and get instant Slack alerts when issues emerge. Theymes MCP turns conversation data into early warning signals.

$ /theymes monitor-sentiment

By the time a sentiment problem shows up in your weekly report, it's already a crisis. Customers have been frustrated for days. Agents are overwhelmed. Leadership is asking questions no one can answer quickly.

Theymes MCP monitors sentiment across all your support channels continuously. When frustration spikes around a specific product, feature, or issue — you know immediately through a Slack alert with full context.

The system goes beyond simple positive/negative scoring. It identifies the specific topics driving sentiment changes, compares current patterns against historical baselines, and flags emerging issues before they reach critical mass.

01

Connect your channels and Slack

Link your support channels to Theymes MCP and choose which Slack channel receives alerts. Configure thresholds for what triggers a notification.

02

Start monitoring

Run /theymes monitor-sentiment to begin continuous analysis. The AI processes conversations in real time and scores sentiment across topics and segments.

03

Act on alerts

When sentiment shifts beyond your configured thresholds, receive a Slack alert with the affected topic, sample conversations, trend direction, and recommended actions.

How it works

Three steps to operational intelligence

01

Connect

Link your support tools through the Theymes MCP server. Works with any MCP-compatible AI assistant.

02

Ask

Run commands in Claude, ChatGPT, or your internal AI tools. Natural language or structured commands, both work.

03

Build your own MCP

Create custom MCP integrations tailored to your workflows. Connect your own tools and data sources.

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What you get

  • Real-time sentiment scoring across all support channels
  • Immediate Slack alerts when sentiment drops below thresholds
  • Topic-level breakdown of what's driving sentiment changes
  • Historical comparison to distinguish noise from real shifts
  • Early detection of emerging product or service issues

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