ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Inference Cost Economics with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Calculate unit economics for AI model deployment, including cost per query, margins, and scale projections.

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 Inference Cost Economics capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Inference Cost Economics.

  1. 01

    Get latency cost tradeoff

    Analyzes the financial impact of choosing faster response times

  2. 02

    Get profitability analysis

    Determines the financial viability of a specific pricing strategy

  3. 03

    Get scale economics projection

    Predicts how cost efficiency changes as the business scales its volume

  4. 04

    Get unit cost

    Calculates the direct operational cost to process a single query

One connector, every AI

AI Inference Cost 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 Inference Cost 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

981ms average. Fast in production.

AI Inference Cost Economics is checked daily against the live service.

Daily averagePeak 1304ms
Sep 5Today
Fastest day
934ms
Slowest day
1304ms
14-day trend
Improving-28%

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

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

AI Inference Cost Economics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_UNk4ChO1CS3YQL7UdVx04v9ViFcqXKNjVSH2VsQr/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 Inference Cost Economics capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-inference-cost-economics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_UNk4ChO1CS3YQL7UdVx04v9ViFcqXKNjVSH2VsQr/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 Inference Cost Economics owners ask.

  • 01

    How does model size affect my costs?

    Larger models require more memory bandwidth and compute, which increases the cost per query. You can use get_unit_cost to see how specific parameter counts impact your budget.

  • 02

    Can I predict savings as my user base grows?

    Yes, the get_scale_economics_projection capability predicts how unit cost reduction occurs as volume increases due to better batch utilization.

  • 03

    How does latency impact my operational budget?

    Lower latency often requires smaller batch sizes or more powerful hardware, which increases costs. Use get_latency_cost_tradeoff to model this impact.