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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Multi-Tenant Cost Modeler with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Calculate infrastructure costs, isolation overhead, and scaling economics for multi-tenant AI workloads.

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 AI Multi-Tenant Cost Modeler capability set.

These are the exact actions your AI can choose when you ask it to work with AI Multi-Tenant Cost Modeler.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Multi-Tenant Cost Modeler.

  1. 01

    Query infrastructure total projection

    Calculates the total projected infrastructure spend for a planned fleet of tenants

  2. 02

    Query noisy neighbor impact

    Estimates the "hidden cost" of over-provisioning required to mitigate performance interference in shared environments

  3. 03

    Query tenant cost breakdown

    Provides a granular view of how much a single tenant costs based on their specific isolation and resource needs

  4. 04

    Query scaling efficiency

    Determines if the current infrastructure strategy is becoming more or less efficient as more tenants are added

One connector, every AI

AI Multi-Tenant Cost Modeler 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 AI Multi-Tenant Cost Modeler 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

993ms average. Fast in production.

AI Multi-Tenant Cost Modeler is checked daily against the live service.

Daily averagePeak 993ms
Sep 5Today
Fastest day
979ms
Slowest day
993ms
14-day trend
Stable-1%

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 AI Multi-Tenant Cost Modeler, so you can see the experience inside your AI.

It does not authenticate your account with AI Multi-Tenant Cost Modeler. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

AI Multi-Tenant Cost Modeler Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_lT6nBhi7MJrVDbFWdfddv5WGjFLplp1Pb1VvONNv/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 — AI Multi-Tenant Cost Modeler capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-multi-tenant-isolation-cost-modeler-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_lT6nBhi7MJrVDbFWdfddv5WGjFLplp1Pb1VvONNv/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? link.label

See all the AI clients this connector works with ↑

FAQ

Questions AI Multi-Tenant Cost Modeler owners ask.

  • 01

    How does isolation level affect my costs?

    Higher isolation levels, such as physical isolation, increase costs because they require dedicated hardware, whereas shared isolation is more cost-efficient but carries higher noisy neighbor risk.

  • 02

    Can I project future spending for a large number of tenants?

    Yes, you can use query_infrastructure_total_projection to calculate the total projected spend, including compute and security costs, for a planned fleet of tenants.

  • 03

    What is the risk of using a shared isolation model?

    Shared models carry a higher risk of noisy neighbor interference. You can use query_noisy_neighbor_impact to estimate the cost of over-provisioning needed to mitigate this risk.

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