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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Cohort Retention Analytics with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Analyze cohort retention curves, average user lifetime, and benchmark performance against industry standards.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 4 capabilities

The complete Cohort Retention Analytics capability set.

These are the exact actions your AI can choose when you ask it to work with Cohort Retention Analytics.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Cohort Retention Analytics.

  1. 01

    Calculate average lifetime

    Determines the expected number of months a user stays active

  2. 02

    Calculate retention curve

    Generates a sequence of data points representing the decay of a cohort over．

  3. 03

    Evaluate retention milestone

    Checks the specific retention percentage for a user at a requested point in time

  4. 04

    Compare performance to benchmark

    Compares a specific metric against the hardcoded industry standard for a chosen product category

Observed, not estimated

640ms average. Fast in production.

Cohort Retention Analytics is checked daily against the live service.

Daily averagePeak 821ms
Aug 20Today
Fastest day
520ms
Slowest day
821ms
14-day trend
Improving-5%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Cohort Retention Analytics, so you can see the experience inside your AI.

It does not authenticate your account with Cohort Retention Analytics. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Cohort Retention Analytics Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_0clZooXkip3nj1SVREyeX8jIZAq7iA6bQySCHT9q/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Cohort Retention Analytics capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "cohort-retention-analytics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_0clZooXkip3nj1SVREyeX8jIZAq7iA6bQySCHT9q/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

FAQ

Questions Cohort Retention Analytics owners ask.

  • 01

    How do I calculate the retention curve?

    Use the calculate_retention_curve capability by providing an array of retention rates where the first element is 1.0 (representing 100% retention at Month 0).

  • 02

    How can I check if my SaaS retention is good?

    Use the compare_performance_to_benchmark capability. Pass 'SaaS' as the product category and your observed metric as the actual value to see if it is 'Above Benchmark' or 'At Risk'.

  • 03

    What does average lifetime represent in this capability?

    The calculate_average_lifetime capability calculates the expected number of months a user remains active by summing all retention rates provided in your input array.

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