Leonardo da Vinci Prover Connector for AI agents.
1 live capability
Force your AI to produce evidence-based product designs.
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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.
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
- Real-world use case 01
Vetting a new signup flow
An agent suggests a 3-step flow.
- Real-world use case 02
Solving a data bottleneck
The agent suggests a buffer.
- 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.
01
1 capability in this set.
Part of 1 available through Leonardo da Vinci Prover.
- 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 previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Leonardo da Vinci Prover, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Leonardo da Vinci Prover for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Leonardo da Vinci Prover URL.
- Step 03
Save and start
Save the connection and enable Leonardo da Vinci Prover in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"leonardo-da-vinci-prover": {
"url": "https://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/mcp"
}
}
} - Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Leonardo da Vinci Prover
Open Agent mode in chat and ask: "Using Leonardo da Vinci Prover, help me...". 1 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"leonardo-da-vinci-prover": {
"url": "https://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/mcp"
}
}
} - Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Leonardo da Vinci Prover
Ask Copilot: "Using Leonardo da Vinci Prover, help me...". 1 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"leonardo-da-vinci-prover": {
"url": "https://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/mcp"
}
}
} - Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Leonardo da Vinci Prover
Open Cascade and ask: "Using Leonardo da Vinci Prover, help me...". 1 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"leonardo-da-vinci-prover": {
"url": "https://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/mcp"
}
}
} - Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Leonardo da Vinci Prover
Ask Cline: "Using Leonardo da Vinci Prover, help me...". 1 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add leonardo-da-vinci-prover --transport http "https://edge.vinkius.com/vk_preview_SOH4W1mNwo69Xl79rZe4v3Ba63vxQhcKozOOxHYW/mcp" - Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Leonardo da Vinci Prover
Ask Claude: "Using Leonardo da Vinci Prover, show me...". 1 tools are ready
Where the request belongs
Work Leonardo da Vinci Prover can move forward.
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.
Product Manager
Uses it to vet 'industry standard' features against actual user friction points on a Tuesday afternoon.
UX Designer
Uses it to move past generic UI patterns and find unique interactions using cross-domain principles.
Creative Director
Uses it to force the AI to provide 3+ distinct creative directions instead of one 'safe' option.
Build the capability set
Add more capabilities.
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Bring your own AI
Change the model, client or framework. Keep Leonardo da Vinci Prover connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
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.
One connection away
Give your agent a direct line to Leonardo da Vinci Prover.
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