ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Model Ensemble Economics with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Calculate the economic efficiency and optimal configuration of AI model ensembles.

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 Model Ensemble Economics capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Model Ensemble Economics.

  1. 01

    Analyze diversity impact

    0), and the cost of the new model. Predicts how adding a diverse model affects the performance-cost ratio

  2. 02

    Calculate ensemble cost

    Calculates the total cost to run a specific ensemble of models

  3. 03

    Evaluate performance efficiency

    Evaluates the performance-cost ratio of an ensemble

  4. 04

    Find optimal ensemble size

    Finds the number of models that maximizes the performance-cost ratio

One connector, every AI

AI Model Ensemble Economics 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 AI Model Ensemble Economics 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

997ms average. Fast in production.

AI Model Ensemble Economics is checked daily against the live service.

Daily averagePeak 1085ms
Sep 5Today
Fastest day
983ms
Slowest day
1085ms
14-day trend
Slowing+10%

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

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

AI Model Ensemble Economics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_FR1jGyQOV1XznddaxHbtSTR4kuwEZmsn6J5W3ULm/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 Model Ensemble Economics capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-model-ensemble-economics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_FR1jGyQOV1XznddaxHbtSTR4kuwEZmsn6J5W3ULm/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 Model Ensemble Economics owners ask.

  • 01

    How do I calculate the total cost of my ensemble?

    You can use the calculate_ensemble_cost capability. Provide the individual costs of each model, the orchestration complexity cost, and any failure handling overhead.

  • 02

    What is the performance-cost ratio?

    It is a metric that measures the performance improvement gained for every dollar spent on inference. You can calculate this using evaluate_performance_efficiency.

  • 03

    Can I find the best number of models to use?

    Yes, the find_optimal_ensemble_size capability iterates through available models to find the specific count that maximizes your performance-cost ratio.