What kind of data does this MCP provide?

It provides industrial reliability metrics, including plant availability, MTBF, production derating predictions, and utilization efficiency.

Which AI clients can I use with this MCP?

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

How does the MCP handle my data?

Vinkius hosts the MCP and manages the connections, so you only need to connect your client once to access the capabilities.

Can I predict production losses?

Yes, the predict_production_derating capability allows your agent to forecast capacity drops based on equipment health and maintenance.

Do I need to host this myself?

No, Vinkius hosts and manages the MCP for you, making it ready to use immediately after connection.

How is plant availability calculated?

Availability is calculated by aggregating the uptime of all selected equipment against the total elapsed time in the specified period, accounting for both planned and unplanned downtime.

Can I predict future production losses?

Yes, you can use the predict_production_derating capability to project how much capacity will drop based on equipment health and scheduled maintenance.

MTBF (Mean Time Between Failures) is a statistical measure of reliability representing the average time elapsed between one failure and the next.

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Connect Plant Availability 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. Turn industrial reliability data into actionable production insights.

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 Plant Availability Model.

01
Calculate plant availability
This capability calculates the current or projected availability percentage for your entire plant.
02
Get reliability metrics
Use this to pull reliability data, such as MTBF, for a specific piece of equipment based on its failure history.
03
Predict production derating
This capability predicts how much your production capacity will drop based on equipment health and scheduled maintenance.
04
Analyze utilization efficiency
This capability analyzes how effectively a piece of equipment is using its available capacity.

Real work

What teams actually run

Maintenance Planning

Predict how much production will drop during upcoming maintenance windows.

Reliability Auditing

Check the MTBF of specific assets to justify equipment replacement.

Capacity Forecasting

Model total plant availability to set realistic production targets.

Utilization Analysis

Determine if specific machines are being underused relative to their capacity.

One connector, every AI

Plant Availability 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.

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

You don't need a client to put Plant Availability 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

925ms average. Fast in production.

Plant Availability Model is checked daily against the live service.

Daily averagePeak 1188ms

Oct 3Today

Fastest day: 724ms
Slowest day: 1188ms
14-day trend: Improving-6%

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 Plant Availability Model, so you can see the experience inside your AI.

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

Plant Availability Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_Ebsz1l3LM9DMrJ7SHjmqKm8QCatTL7Tc90YzlLD9/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 — Plant Availability Model capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "plant-availability-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_Ebsz1l3LM9DMrJ7SHjmqKm8QCatTL7Tc90YzlLD9/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 Plant Availability Model in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Plant Availability Model owners hand off.

This MCP is built for industrial professionals who need to bridge the gap between maintenance logs and production planning.

01
Maintenance Managers
They hand off equipment failure history to the AI to identify reliability trends.
02
Production Planners
They use the AI to forecast capacity losses and schedule around maintenance.
03
Reliability Engineers
They use the AI to calculate MTBF and analyze asset utilization efficiency.

FAQ

Questions Plant Availability Model owners ask.

01
What kind of data does this MCP provide?
It provides industrial reliability metrics, including plant availability, MTBF, production derating predictions, and utilization efficiency.
02
Which AI clients can I use with this MCP?
You can use any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.
03
How does the MCP handle my data?
Vinkius hosts the MCP and manages the connections, so you only need to connect your client once to access the capabilities.
04
Can I predict production losses?
Yes, the predict_production_derating capability allows your agent to forecast capacity drops based on equipment health and maintenance.
05
Do I need to host this myself?
No, Vinkius hosts and manages the MCP for you, making it ready to use immediately after connection.
06
How is plant availability calculated?
Availability is calculated by aggregating the uptime of all selected equipment against the total elapsed time in the specified period, accounting for both planned and unplanned downtime.
07
Can I predict future production losses?
Yes, you can use the predict_production_derating capability to project how much capacity will drop based on equipment health and scheduled maintenance.
08
What is MTBF?
MTBF (Mean Time Between Failures) is a statistical measure of reliability representing the average time elapsed between one failure and the next.

Explore

More in Analytics

Connect Plant Availability Model 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

Calculate plant availability

Get reliability metrics

Predict production derating

Analyze utilization efficiency

What teams actually run

Maintenance Planning

Reliability Auditing

Capacity Forecasting

Utilization Analysis

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

Plant Availability Model Connector

Claude Desktop

Maintenance Managers

Production Planners

Reliability Engineers

What kind of data does this MCP provide?

Which AI clients can I use with this MCP?

How does the MCP handle my data?

Can I predict production losses?

Do I need to host this myself?

How is plant availability calculated?

Can I predict future production losses?

What is MTBF?

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