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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Wine MLF Model with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Models malolactic fermentation progression and predicts completion timelines.

Included with plan

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

Complete set · 4 capabilities

The complete Wine MLF Model capability set.

These are the exact actions your AI can choose when you ask it to work with Wine MLF Model.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Wine MLF Model.

  1. 01

    Compare strain performance

    Compares how different Oenococcus oeni strains would perform under identical wine conditions

  2. 02

    Get optimal conditions

    Suggests the ideal environment to maximize fermentation speed for a specific strain

  3. 03

    Predict mlf progression

    Calculates the expected timeline and acid reduction for a specific wine profile

  4. 04

    Assess mlf risk

    Determines if the current wine conditions are likely to result in a stalled or failed fermentation

Observed, not estimated

825ms average. Fast in production.

Wine MLF Model is checked daily against the live service.

Daily averagePeak 896ms
Aug 27Today
Fastest day
726ms
Slowest day
896ms
14-day trend
Slowing+23%

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 Wine MLF Model, so you can see the experience inside your AI.

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

Wine MLF Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_bfFe0EaSVraOdqUGjoQ71s1EAUzZtS5xqCZIe21l/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 — Wine MLF Model capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "wine-mlf-progression-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_bfFe0EaSVraOdqUGjoQ71s1EAUzZtS5xqCZIe21l/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

FAQ

Questions Wine MLF Model owners ask.

  • 01

    How can I predict if my fermentation will fail?

    You can use the assess_mlf_risk capability. It evaluates environmental inhibitors like high alcohol or SO2 levels to provide a failure risk score.

  • 02

    Can I compare different bacterial strains?

    Yes, the compare_strain_performance capability allows you to compare the degradation rates of multiple Oenococcus oeni strains under the same wine conditions.

  • 03

    What information is needed to estimate completion time?

    To use predict_mlf_progression, you need to provide the initial malic acid concentration, pH, temperature, SO2 level, alcohol content, and the specific strain ID.

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