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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Search Modeler with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Determine if your search improvements are worth the investment.

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 Search Modeler capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Search Modeler.

  1. 01

    Calculate infrastructure investment

    Determines the total monetary cost of the search setup

  2. 02

    Estimate latency impact

    Predicts how much of the user's time budget will be consumed by the proposed search stack

  3. 03

    Evaluate relevance gain

    Calculates the estimated value or quality lift provided by the enhancements

  4. 04

    Get optimization recommendations

    Provides strategic advice on where to cut costs or where to invest for better performance

Observed, not estimated

814ms average. Fast in production.

AI Search Modeler is checked daily against the live service.

Daily averagePeak 974ms
Aug 28Today
Fastest day
744ms
Slowest day
974ms
14-day trend
Improving-11%

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 Search Modeler, so you can see the experience inside your AI.

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

AI Search Modeler Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_4sybgVVU9LYndPjDU66KffbBh9Hw9nUIhzmV6qOz/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 Search Modeler capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-search-investment-modeler-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_4sybgVVU9LYndPjDU66KffbBh9Hw9nUIhzmV6qOz/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

Who it's for

Built for the work AI Search Modeler owners hand off.

This MCP is built for technical leaders and product architects who manage search infrastructure. If you need to justify the budget for AI-powered search features, this capability gives you the hard numbers you need.

  • 01

    Product Manager

    Use this to estimate the user value (relevance gain) versus the cost of a new feature.

  • 02

    Solutions Architect

    Determine the optimal balance between latency, cost, and performance for a given use case.

  • 03

    CTO/VP of Engineering

    Get a clear view of the total cost of ownership (TCO) for advanced search systems.

FAQ

Questions AI Search Modeler owners ask.

  • 01

    Is this just a calculator, or does it provide strategic advice?

    It's both. While it calculates specific metrics like infrastructure cost and latency impact, it also uses those numbers to provide strategic advice on where you should invest or cut spending.

  • 02

    Does it account for embeddings and storage costs?

    Yes. The MCP calculates the total monetary cost, specifically detailing the monthly spend required for both storage and embeddings.

  • 03

    Can I use this for different types of search enhancements?

    You can model enhancements like semantic search, reranking, and hybrid search to see their specific impact on relevance and performance.

  • 04

    What kind of data does it predict?

    It predicts three main things: the total monetary cost, the increase in user latency, and the quality lift, measured as a relevance score improvement.

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