io.github.jeremdecustovox/custovox-sentiment

Official

by jeremdecustovox · HTML

Custovox AI customer sentiment analysis MCP server

MCP Server: io.github.jeremdecustovox/custovox-sentiment

The io.github.jeremdecustovox/custovox-sentiment Model Context Protocol (MCP) server provides customer sentiment analysis through Custovox AI. It is identified by the slug io-github-jeremdecustovox-custovox-sentiment and is focused on analyzing customer sentiment.

🛠️ Key Features

Customer sentiment analysis using Custovox AI

🚀 Use Cases

Analyzing customer sentiment from Custovox AI outputs

⚡ Developer Benefits

Exposes Custovox AI customer sentiment analysis as an MCP server capability

⚠️ Limitations

Available details are limited to the server identity and a short description; no tools, topics, or readme excerpt were provided.

Topics

churn-predictionforecastingmarketingmarketing-analyticsmcpnlpsentiment-analysistopic-modeling

README.md2 KBView on GitHub

custovox.ai — Customer Intelligence MCPs

Listen deeper. Act faster.

NLP-powered MCP servers for business teams. Detect emotions, escalation risks and churn signals from customer calls, reviews, tickets and images.

Built for retail, e-commerce, SaaS and marketing agencies.

What is custovox.ai?

custovox.ai turns customer conversations into actionable business intelligence — using the same AI models used by Google, Amazon, Meta, Uber and Airbnb. Now accessible to any business.

Validated on 83,724 real customer conversations. Academic research — LUMEN Lab / IAE Lille.

MCP Servers

Server	Description	Status
`custovox-sentiment`	Multilingual sentiment (EN/FR/DE/ES/PT-BR)	Coming soon
`custovox-emotion`	6-emotion detection from customer text	Coming soon
`custovox-ticket-scorer`	Priority + sentiment for support tickets	Coming soon
`custovox-review-analyzer`	NLP analysis of Google, G2 & Trustpilot	Coming soon
`custovox-churn-signal`	Churn risk from conversation sequences	Coming soon
`custovox-visual`	Image analysis for hospitality & retail	Coming soon
`custovox-peace`	PEACE™ Escalation Detection 0-100	Proprietary

Use Cases

Market Research — Analyze thousands of reviews across markets and languages
Competitive Analysis — Monitor competitor sentiment automatically
Retail & E-commerce — Detect product issues from photos and reviews
SaaS — Predict churn before it happens
Marketing Agencies — Deliver NLP insights without building your own models
Call Centers — Detect escalation in real time with PEACE™

Supported Languages

English · Français · Deutsch · Español · Português (BR)

Native models — no translation needed.

PEACE™ Algorithm

Score = Emotion x 0.45 + Intention x 0.40 + Sentiment x 0.15

Validated on 83,724 conversations. R2=0.848.

Install

Add to VS Code Add to Cursor

claude_desktop_config.json

json

{
  "mcpServers": {
    "custovox-sentiment": {
      "command": "uvx",
      "args": [
        "custovox-sentiment"
      ]
    }
  }
}