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Connect Wine Mlf Progression Model 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. Predict fermentation timelines and monitor malic acid degradation.

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 · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Wine MLF Model.

  1. 01

    Compare strain performance

    This capability compares how different Oenococcus oeni strains perform under your specific wine conditions.

  2. 02

    Assess mlf risk

    This capability determines if your current wine conditions are likely to cause a stalled or failed fermentation.

  3. 03

    Get optimal conditions

    This capability suggests the ideal environmental parameters to maximize fermentation speed for a specific strain.

  4. 04

    Predict mlf progression

    This capability calculates the expected timeline and acid reduction for a given wine profile.

Real work

What teams actually run

01

Predicting Completion

Use the capability to estimate exactly how many days are left until MLF is finished.

02

Strain Selection

Compare how different Oenococcus oeni strains will behave in your current wine.

03

Risk Mitigation

Check if high alcohol or SO2 levels will cause your fermentation to stall.

04

Process Optimization

Find the best temperature and pH settings to speed up a specific strain.

One connector, every AI

Wine MLF Model 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 Wine MLF Model 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

883ms average. Fast in production.

Wine MLF Model is checked daily against the live service.

Daily averagePeak 1204ms
Oct 3Today
Fastest day
722ms
Slowest day
1204ms
14-day trend
Slowing+38%

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

Guided setup for Claude? Set up Wine MLF Model in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Wine MLF Model owners hand off.

This MCP is built for professionals managing wine fermentation processes who need rapid, data-backed predictions.

  • 01

    Winemakers

    They hand off wine chemistry data to the AI to get fermentation timelines.

  • 02

    Enologists

    They use the capability to model strain performance and acid reduction rates.

  • 03

    Cellar Managers

    They use risk assessments to monitor for potential fermentation failures.

FAQ

Questions Wine MLF Model owners ask.

  • 01

    What can this MCP predict regarding malolactic fermentation?

    It predicts the number of days until completion, the malic acid degradation rate, and the expected diacetyl production.

  • 02

    How does the capability handle different yeast strains?

    It allows you to compare the performance of different Oenococcus oeni strains and find the optimal environmental conditions for a specific one.

  • 03

    Can it help prevent fermentation failure?

    Yes, the risk assessment capability identifies if current wine conditions, such as high alcohol or SO2, are likely to cause a stalled fermentation.

  • 04

    Which AI clients can I use with this MCP?

    You can use this MCP with any compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 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 your client.

  • 06

    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.

  • 07

    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.

  • 08

    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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