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Connect Product Market Fit Diagnostic Engine to your AI

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Get a quantitative health score for your product.

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

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Product-Market Fit Engine.

  1. 01

    Analyze retention health

    Checks if your user base is actually stabilizing or if you're losing people too fast.

  2. 02

    Calculate pmf score

    Generates a primary quantitative score to assess your overall product health.

  3. 03

    Get improvement priorities

    Pinpoints the specific business areas that need work to improve your market fit.

  4. 04

    Evaluate growth efficiency

    Determines if your growth is driven by real market demand or just paid spend.

Real work

What teams actually run

01

Post-Launch Validation

Check if your new feature or product actually has the market pull you expected.

02

Scaling Decisions

Verify that your retention is stable before you increase your marketing budget.

03

Churn Investigation

Use retention analysis to see exactly when and why users are dropping off.

04

Investor Reporting

Generate quantitative health assessments to back up your growth claims.

One connector, every AI

Product-Market Fit Engine works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Product-Market Fit Engine to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

897ms average. Fast in production.

Product-Market Fit Engine is checked daily against the live service.

Daily averagePeak 1074ms
Oct 3Today
Fastest day
674ms
Slowest day
1074ms
14-day trend
Slowing+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 Product-Market Fit Engine, so you can see the experience inside your AI.

It does not authenticate your account with Product-Market Fit Engine. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Product-Market Fit Engine Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_Fumw4rkLtbXjlnA8Eys2PwFyMXKwB4UfbOoTT0Er/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 — Product-Market Fit Engine capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "product-market-fit-diagnostic-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_Fumw4rkLtbXjlnA8Eys2PwFyMXKwB4UfbOoTT0Er/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

Guided setup for Claude? Set up Product-Market Fit Engine in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Product-Market Fit Engine owners hand off.

This MCP is built for product leaders who need to validate their roadmap with hard data. It helps move the conversation from opinions to metrics.

  • 01

    Product Managers

    They hand off retention and NPS data to get a clear readiness score.

  • 02

    Growth Leads

    They use it to check if their acquisition spend is actually building a stable user base.

  • 03

    Founders

    They use the diagnostic to decide whether to pivot or scale.

FAQ

Questions Product-Market Fit Engine owners ask.

  • 01

    What metrics does the PMF score use?

    The score is calculated using retention curves, the Sean Ellis test, and NPS data.

  • 02

    How do I use this with Claude?

    You connect the MCP through the Vinkius platform, and then you can talk to Claude about your metrics directly.

  • 03

    Can this tell me if my growth is sustainable?

    Yes, the evaluate_growth_efficiency capability determines if your growth is driven by market demand or just paid spend.

  • 04

    What if my retention is dropping?

    You can use the analyze_retention_health capability to see if your user base is stabilizing or leaking.

  • 05

    Does this work with any AI client?

    It works with any MCP-compatible client, including Claude, Cursor, and Windsurf.

  • 06

    How is the PMF score calculated?

    The score is a weighted composite of user retention, NPS, organic growth, referral rates, and the Sean Ellis 'very disappointed' percentage via the calculate_pmf_score capability.

  • 07

    Can I analyze my retention curve?

    Yes, use analyze_retention_health by providing a sequence of retention percentages to determine if your cohort is stabilizing or leaking.

  • 08

    What are improvement priorities?

    The get_improvement_priorities capability identifies the most critical areas for intervention based on your current metrics deviation from ideal benchmarks.

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