mcpbeat Sign in

Customer Retention LTV MCP Server

local only

Customer Retention LTV runs on your own machine — the client starts it, so there is no endpoint to ping. 63 installs a week from pypi.

Customer LTV, churn risk, repurchase, lifecycle email, and winback intelligence.

Installs per day peak 22 · avg 10 · -12% w/w
a month agotoday
63
Installs / week
pypi · customer-retention-ltv-mcp
Stars
on GitHub
Last commit
0 releases in 90 days
License
language unknown

Nothing serious here today

Today is the operative word: we check Customer Retention LTV every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Three servers free · no card

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add customer-retention-ltv -- uvx customer-retention-ltv-mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "customer-retention-ltv": {
      "args": [
        "customer-retention-ltv-mcp"
      ],
      "command": "uvx"
    }
  }
}
~/.codex/config.toml
[mcp_servers.customer-retention-ltv]
command = "uvx"
args = ["customer-retention-ltv-mcp"]
.cursor/mcp.json
{
  "mcpServers": {
    "customer-retention-ltv": {
      "args": [
        "customer-retention-ltv-mcp"
      ],
      "command": "uvx"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "customer-retention-ltv": {
      "args": [
        "customer-retention-ltv-mcp"
      ],
      "command": "uvx"
    }
  }
}

This one needs environment variables set before it will start: EARNALL_MCP_LICENSE_KEY (License key from AtulHritik-Mcp-Customer-Retention-Ltv purchase page.), EARNALL_MCP_ACTIVATION_ID (Optional stable private install ID for this user/device.), EARNALL_MCP_LICENSE_API (License validation endpoint.). The author declared them in the registry entry; get the values from the project itself.

Alternatives to Customer Retention LTV

same job, measured the same way
Phano Intelligence Platform
by phano

Read-only account intelligence for Customer Success and Account Management teams.

answering
Content Repurposer
by as-the-geek-learns

Repurpose content into Twitter threads, LinkedIn posts, Substack notes, email, and video.

37 installs/wk local only
Shipmail MCP
by shipmail-to

Shipmail MCP server for AI agent custom-domain email inboxes with REST API and webhooks.

491 installs/wk answering
MCP Whoisxmlapi
by whois-api-llc

32 WHOIS, DNS, IP, threat intelligence, email, and bulk tools for AI agents via WhoisXML API.

238 installs/wk local only
Backengine MCP
by backengine

Surface customer & prospect context from Slack, email, transcripts and tickets in any MCP client.

answering
MAILTYPE — Email Domain Capability Intelligence
by gsterlingpress

Email-domain intelligence: MX capability, provider, disposable status, SPF, DMARC, and MTA-STS.

answering
SendPulse
by sendpulse-mcp

Empower AI agents with SendPulse email, CRM, chatbot, SMTP, and course automation

answering
Proofpoint
by wyre-ai

MCP server for Proofpoint TAP — threat intelligence, forensics, quarantine, and email security.

local only

Customer Retention LTV — questions

Answers built from our own checks of this server.

Why is there no uptime for Customer Retention LTV?
Customer Retention LTV runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package customer-retention-ltv-mcp was installed 63 times last week.
How do I connect Customer Retention LTV?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It runs locally, so the command pulls customer-retention-ltv-mcp straight from pypi; nothing to host, nothing to sign up for.
How many people use Customer Retention LTV?
The pypi package customer-retention-ltv-mcp was installed 63 times in the last week. Week over week that is -12%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.