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Connect Product Discovery Prover to ChatGPT and Claude

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. Stop wasting engineering hours on unproven product assumptions.

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 · 1 capability

We ship only the actions that matter.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through Product Discovery Prover.

  1. 01

    Validate product discovery

    This capability runs a structured audit of your product idea by cross-checking problem evidence, behavioral segments, competitor gaps, purchase intent, and MVP scope. It rejects any input that contains self-contradictory logic or lacks concrete data like search volume or financial commitment.

Real work

What teams actually run

01

New Feature Validation

Test if a proposed feature solves a real pain point before adding it to the sprint.

02

Market Entry Decisions

Verify if a new industry segment has enough willingness-to-pay to justify a move.

03

MVP Definition

Shrink a massive product roadmap into a single, testable, one-week experiment.

04

Competitor Analysis

Audit existing workflows to find the specific gaps that your product must fill to win.

Automate a task

Put Product Discovery Prover to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Product Discovery Prover 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 Discovery Prover 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

926ms average. Fast in production.

Product Discovery Prover is checked daily against the live service.

Daily averagePeak 1152ms
Oct 3Today
Fastest day
714ms
Slowest day
1152ms
14-day trend
Slowing+14%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 1 capability arrives 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 Discovery Prover, so you can see the experience inside your AI.

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

Product Discovery Prover Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_oRfntTCBhavUOPmcOZLkfPw8gtNLViGrf1SALzQt/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 Discovery Prover capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "product-discovery-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_oRfntTCBhavUOPmcOZLkfPw8gtNLViGrf1SALzQt/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 Discovery Prover in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Product Discovery Prover owners hand off.

This MCP is built for teams that prioritize capital efficiency and evidence-based decision making.

  • 01

    Product Managers

    They hand off raw market hypotheses to the MCP to get a formal validation verdict.

  • 02

    Founders

    They use it to prevent committing engineering resources to unproven ideas.

  • 03

    Product Designers

    They use the behavioral segmentation output to define precise user workflows.

FAQ

Questions Product Discovery Prover owners ask.

  • 01

    How does this MCP prevent engineering waste?

    It acts as a gatekeeper that rejects product ideas unless they are backed by specific evidence, behavioral segments, and proven purchase intent.

  • 02

    What is the difference between interest and intent in this capability?

    The capability treats compliments and waitlist signups as interest, while it requires pre-orders, LOIs, or pilot agreements to verify actual purchase intent.

  • 03

    Can I use this with Claude or Cursor?

    Yes, you can connect this MCP to any compatible client including Claude, Cursor, and Windsurf.

  • 04

    What happens if my product idea is rejected?

    A rejection indicates a blind spot in your discovery. You must fix the problem evidence, segment, or MVP scope before proceeding.

  • 05

    Does this replace market research?

    It provides a structured framework to process your market research into actionable, testable product hypotheses.

  • 06

    Why does the capability reject demographic segments?

    Because demographics are useless for product design. 'Millennials' is a marketing category, not a workflow. We demand behavioral segments because they isolate users actively experiencing the exact pain point you intend to solve.

  • 07

    What qualifies as valid purchase intent?

    Money or legally binding ink. Polite compliments and 'I would use this' are false signals that kill startups. We require active commitment: credit cards on file, signed B2B Letters of Intent (LOIs), or cash deposits.

  • 08

    How should an MVP be scoped?

    As a single-variable experiment. Drop the settings panels, user profiles, and polished UI. The MVP must isolate and test the core value hypothesis. Use manual back-end workarounds to deliver the outcome without building the platform.

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