What can this MCP do for snowboard design?

It models vibration absorption and ride stability using viscoelastic principles. You can use it to optimize layer placement and predict chatter thresholds.

Which AI clients can use this MCP?

You can use this with any MCP-compatible client like Claude, Cursor, Windsurf, or VS Code.

How do I optimize my board's dampening layers?

You can use the optimize_layer_placement capability to evaluate how moving a layer within the stack affects performance.

Can I predict when a board will chatter?

Yes, the chatter_threshold capability predicts the speed at which a board will experience unstable oscillations.

Do I need to host the MCP myself?

No, Vinkius hosts and manages the MCP for you, so it is ready to use as soon as you connect.

How do I calculate the vibration reduction for a new material?

You can use the vibration_reduction capability by providing the material's loss factor and stiffness as a JSON string, along with the layer thickness and target frequency.

What determines the ride smoothness score?

The score is determined by the ride_smoothness capability, which evaluates the vibration reduction percentage against the current riding speed and the calculated chatter threshold.

Can I optimize where the dampening layer is placed in the board?

Yes, the optimize_layer_placement capability allows you to evaluate how different stack depths affect the effectiveness factor for a specific vibration frequency.

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Connect Snowboard Dampening Layers 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. Model vibration absorption and stability for better board construction.

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.

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.

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 Snowboard Dampening Layers.

01
Chatter threshold
This capability predicts the specific speed where a snowboard begins to experience unstable oscillations.
02
Optimize layer placement
Use this to evaluate how shifting a dampening layer within the board stack changes overall performance.
03
Ride smoothness
This capability provides a qualitative score for the riding experience at a given speed.
04
Vibration reduction
This capability calculates the amount of vibration energy absorbed by a specific material and thickness.

Real work

What teams actually run

Material Testing

Compare how a 2mm layer versus a 3mm layer absorbs vibration.

High-Speed Stability

Determine if a new core material will cause chatter at high speeds.

Stack Optimization

Test different depths for dampening layers to maximize performance.

Ride Quality Assessment

Score the smoothness of a design based on predicted vibration levels.

One connector, every AI

Snowboard Dampening Layers 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.

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

You don't need a client to put Snowboard Dampening Layers 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

852ms average. Fast in production.

Snowboard Dampening Layers is checked daily against the live service.

Daily averagePeak 1131ms

Oct 3Today

Fastest day: 735ms
Slowest day: 1131ms
14-day trend: Stable-4%

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 Snowboard Dampening Layers, so you can see the experience inside your AI.

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

Snowboard Dampening Layers Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_M1r6hcslBdTDMlF7pK48bEHqus2x4gf8jCJct7nt/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — Snowboard Dampening Layers capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "snowboard-dampening-layers-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_M1r6hcslBdTDMlF7pK48bEHqus2x4gf8jCJct7nt/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 Snowboard Dampening Layers in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Snowboard Dampening Layers owners hand off.

This MCP is built for engineers designing high-performance winter sports equipment.

01
Snowboard Engineer
Hands off material specs to the AI to run vibration simulations.
02
Product Designer
Uses the capability to optimize the internal stack of a board.
03
Material Scientist
Tests how specific viscoelastic properties translate to ride feel.

FAQ

Questions Snowboard Dampening Layers owners ask.

01
What can this MCP do for snowboard design?
It models vibration absorption and ride stability using viscoelastic principles. You can use it to optimize layer placement and predict chatter thresholds.
02
Which AI clients can use this MCP?
You can use this with any MCP-compatible client like Claude, Cursor, Windsurf, or VS Code.
03
How do I optimize my board's dampening layers?
You can use the optimize_layer_placement capability to evaluate how moving a layer within the stack affects performance.
04
Can I predict when a board will chatter?
Yes, the chatter_threshold capability predicts the speed at which a board will experience unstable oscillations.
05
Do I need to host the MCP myself?
No, Vinkius hosts and manages the MCP for you, so it is ready to use as soon as you connect.
06
How do I calculate the vibration reduction for a new material?
You can use the vibration_reduction capability by providing the material's loss factor and stiffness as a JSON string, along with the layer thickness and target frequency.
07
What determines the ride smoothness score?
The score is determined by the ride_smoothness capability, which evaluates the vibration reduction percentage against the current riding speed and the calculated chatter threshold.
08
Can I optimize where the dampening layer is placed in the board?
Yes, the optimize_layer_placement capability allows you to evaluate how different stack depths affect the effectiveness factor for a specific vibration frequency.

Explore

More in Engineering

Connect Snowboard Dampening Layers to Claude, Cursor, ChatGPT & more

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

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-04

Chatter threshold

Optimize layer placement

Ride smoothness

Vibration reduction

What teams actually run

Material Testing

High-Speed Stability

Stack Optimization

Ride Quality Assessment

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

Snowboard Dampening Layers Connector

Claude Desktop

Snowboard Engineer

Product Designer

Material Scientist

What can this MCP do for snowboard design?

Which AI clients can use this MCP?

How do I optimize my board's dampening layers?

Can I predict when a board will chatter?

Do I need to host the MCP myself?

How do I calculate the vibration reduction for a new material?

What determines the ride smoothness score?

Can I optimize where the dampening layer is placed in the board?

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