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Connect Leonardo da Vinci 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 accepting mediocre, single-perspective designs from your AI.

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 Leonardo da Vinci Prover.

  1. 01

    Validate davinci design

    This capability subjects your design or architecture to a five-step rigor check. It forces your AI to prove it has performed direct observation, connected unrelated disciplines, built a testable prototype, exploited constraints, and explored multiple variations.

Real work

What teams actually run

01

UX Flow Optimization

Validate that a new checkout or signup flow is based on actual user friction rather than assumptions.

02

System Architecture

Ensure a new data pipeline or infrastructure design accounts for real-world bottlenecks and constraints.

03

Product Strategy

Test if a product roadmap is actually solving a documented problem or just following a trend.

04

Creative Problem Solving

Use cross-domain insights to find non-obvious solutions to complex engineering or design challenges.

Automate a task

Put Leonardo da Vinci 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

Leonardo da Vinci 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 Leonardo da Vinci 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

963ms average. Fast in production.

Leonardo da Vinci Prover is checked daily against the live service.

Daily averagePeak 1279ms
Oct 3Today
Fastest day
714ms
Slowest day
1279ms
14-day trend
Improving-9%

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 Leonardo da Vinci Prover, so you can see the experience inside your AI.

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

Leonardo da Vinci Prover Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/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 — Leonardo da Vinci Prover capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "leonardo-da-vinci-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/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 Leonardo da Vinci Prover in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Leonardo da Vinci Prover owners hand off.

This MCP is for professionals who need to move beyond the first, most obvious answer an AI provides.

  • 01

    Product Designers

    They hand off user flow concepts to ensure they aren't just following generic patterns.

  • 02

    Systems Architects

    They use it to validate that technical structures account for real-world constraints and varied edge cases.

  • 03

    Creative Directors

    They apply it to ensure creative concepts are grounded in observation and multi-disciplinary thinking.

FAQ

Questions Leonardo da Vinci Prover owners ask.

  • 01

    How does this MCP differ from a standard design prompt?

    Standard prompts allow the AI to guess based on training data. This MCP uses a structured decision matrix to reject any answer that lacks direct observation, cross-domain insight, or a testable prototype.

  • 02

    What happens if my AI's design is rejected?

    The capability provides a specific verdict, such as INTERDISCIPLINARY_BLIND or PROTOTYPE_SKIPPED, telling you exactly which part of the design process failed so you can fix it.

  • 03

    Can I use this with any AI client?

    Yes, it works with any MCP-compatible client like Claude, Cursor, or Windsurf once connected through Vinkius.

  • 04

    Does this replace the design process?

    No, it acts as a rigor engine that forces your agent to follow a more disciplined, Da Vinci-inspired methodology.

  • 05

    What is a 'Decision Pivot'?

    A pivot is one of five mandatory checks: observation, connection, prototype, constraint, and variation. A design must pass all five to be considered proven.

  • 06

    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.

  • 07

    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.'

  • 08

    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.

Explore

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