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churn-predictor-ai-mcp

churn-predictor-ai-mcp

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github.com/CSOAI-ORGBusiness & Marketing0Updated 8w ago
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About churn-predictor-ai-mcp

churn-predictor-ai-mcp is an MCP server for customer churn prediction and retention analytics. It provides tools for individual and batch churn predictions and customer risk checks.

Key features

  1. 01Predict customer churn
  2. 02Run batch churn predictions
  3. 03Retrieve customer risk

Use cases

  1. 01Estimate an individual customer's churn risk
  2. 02Process churn predictions for multiple customers
  3. 03Review a customer's risk information

MCP support

Exposes churn prediction and customer risk tools to MCP clients, including predict_churn, batch_predict_churn, and get_customer_risk. It can be configured to run over stdio.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "csoai-org-churn-predictor-ai": {
      "command": "uvx",
      "args": [
        "churn-predictor-ai-mcp"
      ]
    }
  }
}
Run commanduvx churn-predictor-ai-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypichurn-predictor-ai-mcp1.0.10

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Scorecard: 74/100

Churn Predictor Ai MCP

MEOK AI Labs GSPC License PyPI

Comprehensive customer churn prediction and retention analytics

Comprehensive customer churn prediction and retention analytics.

🚀 Quick Start

# Install via pip
pip install churn_predictor_ai_mcp

# Or install via Smithery
npx -y @smithery/cli@latest install churn-predictor-ai-mcp --client claude

✨ Features

  • MCP protocol compliant
  • Easy installation
  • Well-documented API
  • Production-ready
  • Active maintenance

📖 Documentation

🛡️ Compliance

This MCP server is built with EU AI Act compliance built-in:

  • ✅ Article 9 — Risk Management System
  • ✅ Article 13 — Transparency & Instructions for Use
  • ✅ Article 15 — Bias Detection & Testing
  • ✅ Article 26 — FRIA Support (where applicable)
  • ✅ Article 50 — AI Content Watermarking (where applicable)

Need help getting compliant? Book a free 15-min diagnostic →

🏢 Enterprise

Need custom development, SLA guarantees, or white-label deployment?

  • Pro: $99/mo — Full MCP suite + EU AI Act tracking
  • Enterprise: $499/mo — Custom dev + SLA + Dedicated support

View Pricing → | Contact Sales →

🤝 Part of the MEOK Ecosystem

This server is part of the MEOK AI Labs ecosystem — 300+ MCP servers for sovereign AI governance.

DomainPurpose
councilof.aiEU AI Act compliance marketplace
safetyof.aiAI safety & monitoring
meok.aiSovereign AI platform
cobolbridge.aiLegacy modernization

📜 License

MIT © CSOAI-ORG

Built with 💜 by MEOK AI Labs · UK Companies House 16939677

Each tier above the free self-host adds HMAC-signed attestations verifiable at `verify.meok.ai`. Linux Foundation governance on the A2A spine means EU regulated buyers can deploy without vendor-lock-in objections.

💸 Try MEOK in 30 seconds — instant buy ladder

TierPriceWhat you getStripe
Smoke test£1Signed sample MCP-Hardening report + Article 50 PDFhttps://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j
Quick Kit£9EU AI Act Article 50 implementation guide (C2PA + EU-Icon)https://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j
Founder Call£2930-min 1-on-1 with the founderhttps://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j

Refundable. UK Stripe — VAT-clean. Builds on the 81-MCP MEOK fleet. Verify any signed report at https://meok.ai/verify.

Configuration

Add to your claude_desktop_config.json (Claude Desktop) or your MCP client config:

{
  "mcpServers": {
    "churn-predictor-ai-mcp": {
      "command": "uvx",
      "args": ["churn-predictor-ai-mcp"]
    }
  }
}

Or: pip install churn-predictor-ai-mcp then run the churn-predictor-ai-mcp command (stdio transport).

Examples

Once configured, ask your assistant, for example:

  • "Use predict_churn to …"
  • "Use batch_predict_churn to …"
  • "Use get_customer_risk to …"

Comments

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