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Vinkius

Leonardo da Vinci Prover Connector for AI agents.

1 live capability

Force your AI to produce evidence-based product designs.

Live agent request Leonardo da Vinci Prover / Connector

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AI Agent

Why people use Leonardo da Vinci Prover

Leonardo da Vinci Prover: Stop Generic AI Design

This Connector flips the script. It forces the agent to stop guessing and start proving. Instead of a list of features, the agent must provide documented observations, cross-domain connections, and a testable artifact. You get a design that's been stress-tested against your actual constraints, giving you a defensible strategy instead of a generic suggestion.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

That your agent can no longer guess; it has to prove its logic through a rigorous design framework.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Vetting a new signup flow

    An agent suggests a 3-step flow.

  2. Real-world use case 02

    Solving a data bottleneck

    The agent suggests a buffer.

  3. Real-world use case 03

    Designing a limited UI

    A client has a tiny screen.

Complete set · 1capability

The complete Leonardo da Vinci Prover capability set.

These are the exact actions your AI can choose when you ask it to work with Leonardo da Vinci Prover.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through Leonardo da Vinci Prover.

  1. 01 Capability

    Validate davinci design

    Forces the AI to follow a rigorous five-step design methodology. It validates that your agent has cited real observations and provided three distinct variations.

Set up in minutes

One URL. Then ask Leonardo da Vinci Prover to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Leonardo da Vinci Prover from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it Leonardo da Vinci Prover, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Leonardo da Vinci Prover for the conversation.

Where the request belongs

Work Leonardo da Vinci Prover can move forward.

Built around the request

For product leads and creative directors who are tired of generic AI outputs and need a way to force their agents to produce high-fidelity, evidence-based design work.

01

Product Manager

Uses it to vet 'industry standard' features against actual user friction points on a Tuesday afternoon.

02

UX Designer

Uses it to move past generic UI patterns and find unique interactions using cross-domain principles.

03

Creative Director

Uses it to force the AI to provide 3+ distinct creative directions instead of one 'safe' option.

Build the capability set

Each Connector adds new actions and data without changing how you work.

Browse Connectors
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01 1 capability

Breakthrough Ideation Prover

AI agents default to safe, obvious ideas or hallucinate impossible ones. This capability forces breakthrough ideation: challenge convention with facts, integrate real constraints, map a concrete roadmap, and prove feasibility for every blocker. Radical AND realizable.

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02 1 capability

Systems Thinking Prover

AI thinks in straight lines. This engine is a 6-pivot cognitive trap that forces the LLM to map feedback loops, second-order effects, and bottlenecks before proposing any architectural change.

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03 1 capability

First Principles Prover

LLMs reason by analogy, copying industry norms. This engine is a 6-pivot cognitive trap that forces the agent to discard jargon and derive original solutions exclusively from physical, mathematical, or logical axioms.

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04 1 capability

UI/UX Excellence Prover

AI agents generate flat, lifeless interfaces: decorative shadows, linear animations, buttons without hover states, chaotic spacing, and accessibility theater. This capability enforces 2026-era excellence: spatial hierarchy with Liquid Glass, spring-based motion, 8-state microinteractions, 8.

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05 1 capability

Steve Jobs Vision Prover

A product had settings menus with 47 options and 15 integrations. This capability forces it to kill features, absorb complexity, and own the whole experience.

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06 10 capabilities

Lanhu

Product design collaboration platform. manage design files, handoffs, and team feedback via AI.

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Bring your own AI

Change the model, client or framework. Keep Leonardo da Vinci Prover connected.

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Before you connect

Questions about Leonardo da Vinci Prover.

The practical details behind the request, access and result.

What does the Leonardo da Vinci Prover MCP actually do?

It forces your AI agent to follow a rigorous five-step design methodology. It ensures your agent provides evidence, cross-domain connections, and testable prototypes instead of just giving you a generic summary.

How does it stop my AI from giving generic answers?

It detects 'lazy' AI thinking. If the agent tries to rely on 'best practices' without citing real observations, the Connector rejects the answer and forces the agent to find real data.

Can it help with my specific product design?

Yes, it's built for high-stakes product design. It helps you move from vague ideas to defensible, evidence-based concepts by forcing the AI to account for your specific budget and technical limits.

What is the 'Da Vinci Method' in this capability?

It's a methodology for creative engineering. It requires the AI to observe a phenomenon, connect it to an unrelated field, build a prototype, exploit constraints, and provide multiple variations.

How does it handle my budget constraints?

It treats your limitations as creative fuel. Instead of the AI saying 'if only we had more money,' it forces the agent to design the best possible solution within your specific constraints.

Will it provide multiple design options?

Yes, it mandates that the agent provides at least three distinct variations. Each variation comes with a clear analysis of its trade-offs so you can make an informed choice.

How does it help with cross-domain innovation?

It forces the agent to look outside your industry. It might pull insights from fluid dynamics, music theory, or game design to solve a product problem in a way that a single-domain approach never could.

Is this only for visual design?

No. Da Vinci was an engineer, anatomist, architect, and painter. This capability applies his method to any creative problem: process design, product design, experience flows, organizational structure, service design, operational improvement. The 5 pivots. observe, connect domains, prototype, exploit constraints, iterate. apply wherever a human designs something for other humans.

What counts as cross-domain synthesis?

Two genuinely different disciplines, not sub-fields. Frontend and backend are the same domain. Psychology and software architecture are different domains. Biology and data modeling are different domains. Music theory and UI rhythm are different domains. The insight must transfer. not 'I thought about psychology' but 'cognitive load theory from psychology limits my dashboard to 7±2 elements per view.'

Why does it require 3+ variations?

Da Vinci's notebooks contain 50+ sketches of a single muscle group. One answer is a reflex. three variations with annotated trade-offs is design. Variation A optimizes for simplicity. Variation B optimizes for performance. Variation C asks 'what if the opposite were true?' The comparison reveals which trade-offs you are willing to make and which you are not.

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