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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Economics Engine with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Determine the optimal, cost-effective processing architecture for your workload.

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 Economics Engine capability set.

These are the exact actions your AI can choose when you ask it to work with AI Economics Engine.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Economics Engine.

  1. 01

    Analyze processing economics

    Calculates the fundamental cost and margin differences between Batch and Real-time modes

  2. 02

    Calculate spot impact

    Predicts how changes in spot instance availability will affect the total cost of the batch processing mode

  3. 03

    Evaluate sla compliance

    Determines if a specific workload configuration can meet the required latency requirements

  4. 04

    Optimize workload split

    Identifies the most cost-effective distribution of tasks between Batch and Real-time modes

One connector, every AI

AI Economics Engine 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 Economics Engine 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

881ms average. Fast in production.

AI Economics Engine is checked daily against the live service.

Daily averagePeak 881ms
Sep 6Today
Fastest day
881ms
Slowest day
881ms
14-day trend
Stable0%

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 Economics Engine, so you can see the experience inside your AI.

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

AI Economics Engine Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_zitl9X7jqfGsGeIEjtCU1TJU7r89nl3lLRd0tym5/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 Economics Engine capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-batch-vs-real-time-economics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_zitl9X7jqfGsGeIEjtCU1TJU7r89nl3lLRd0tym5/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 ↑

Who it's for

Built for the work AI Economics Engine owners hand off.

Cloud Architects and ML Engineers use this MCP when they need to prove the financial viability of their AI infrastructure. If you're responsible for keeping compute costs low while maintaining strict performance guarantees, this capability gives you the data to justify your architecture choices.

  • 01

    Cloud Architect

    Determines the optimal mix of batch and real-time resources to meet budget and performance goals.

  • 02

    ML Engineer

    Models the economic impact of different processing modes to select the most efficient deployment strategy.

  • 03

    FinOps Specialist

    Calculates potential cost savings by factoring in variable costs like spot instance availability.

FAQ

Questions AI Economics Engine owners ask.

  • 01

    How do I calculate the cost difference between batch and real-time AI processing?

    You use the analyze_processing_economics capability. This function calculates the fundamental cost and margin differences, helping you see which mode is more profitable for your specific workload.

  • 02

    Does this MCP account for cloud spot instance pricing?

    Yes. The calculate_spot_impact capability predicts how changes in spot instance availability will affect your total cost when running tasks in batch mode.

  • 03

    What if my workload has strict latency requirements?

    You can use evaluate_sla_compliance. This capability checks if your proposed configuration meets your required latency SLAs, ensuring you don't deploy something that will fail performance checks.

  • 04

    Is this for general AI cost modeling?

    No. This MCP is specifically designed to compare the economic trade-offs between two distinct processing modes: high-throughput Batch and low-latency Real-time.

  • 05

    Can I find the best mix of batch and real-time tasks?

    Absolutely. The optimize_workload_split capability identifies the most cost-effective distribution of tasks between the two modes, giving you a concrete plan.

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