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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use RAG Cost Estimator with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Calculate upfront and monthly costs for RAG system deployment.

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 RAG Cost Estimator capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through RAG Cost Estimator.

  1. 01

    Analyze scalability factors

    Evaluates how costs and performance will behave as the system grows

  2. 02

    Calculate upfront investment

    Estimates the initial one-time cost to build and deploy the RAG pipeline

  3. 03

    Compare architectures

    Compares two different technical setups to identify the most cost-effective configuration

  4. 04

    Estimate monthly operations

    Projects the recurring monthly costs required to keep the RAG system running

Observed, not estimated

851ms average. Fast in production.

RAG Cost Estimator is checked daily against the live service.

Daily averagePeak 1154ms
Aug 27Today
Fastest day
776ms
Slowest day
1154ms
14-day trend
Improving-33%

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 RAG Cost Estimator, so you can see the experience inside your AI.

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

RAG Cost Estimator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_HZVbUNVY2cZnkgb1Ea9JkXEXbBrk8axXl1VttWtf/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 — RAG Cost Estimator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "rag-implementation-cost-estimator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_HZVbUNVY2cZnkgb1Ea9JkXEXbBrk8axXl1VttWtf/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

FAQ

Questions RAG Cost Estimator owners ask.

  • 01

    How does document volume affect the cost?

    Higher document volume increases both upfront costs for embedding and monthly costs for vector database storage.

  • 02

    Can I compare two different RAG setups?

    Yes, use the compare_architectures capability to evaluate the 12-month total cost difference between two technical configurations.

  • 03

    What factors influence monthly operational costs?

    Monthly costs are driven by document volume, the chosen vector database tier, query frequency, and the embedding model complexity.

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