Yes, Custovox Ai is free to use.

How do I install Custovox Ai?

Custovox Ai is a local plugin. Install it using PyPI package: custovox-churn-signal and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

Is Custovox Ai safe to use?

Custovox Ai was flagged by MCP Marketplace's security scan, scoring 3.3/10 (high risk). It has 13 high or critical findings to review. Review the security report on this page carefully before installing it.

What AI apps work with Custovox Ai?

Custovox Ai uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Custovox Ai MCP Server

by Jeremdecustovox

Developer ToolsUse Caution3.3MCP RegistryLocal

Free

Server data from the Official MCP Registry

custovox.ai churn risk detection MCP server: 0-100 score from customer message sequences

About

custovox.ai churn risk detection MCP server: 0-100 score from customer message sequences

Security Report

3.3

Use Caution3.3High Risk

The servers contain no hardcoded credentials and their tools process only the supplied text. The main concerns are default-on, undisclosed usage telemetry sent to a third-party Google Apps Script endpoint in the sentiment server, and a server-side request forgery risk in the visual server's image loader. These issues keep the score below 7.0 despite otherwise clean code. Supply chain analysis found 18 known vulnerabilities in dependencies (1 critical, 12 high severity). Package verification found 1 issue.

19 files analyzed · 25 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-jeremdecustovox-custovox-churn-signal": {
      "args": [
        "-y",
        "custovox-tools"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

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.

Reviews

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4.8

Local

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