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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Embedding Dimension Optimizer with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. A deterministic capability to balance embedding quality, latency, and storage efficiency.

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 · 3 capabilities

The complete Embedding Dimension Optimizer capability set.

These are the exact actions your AI can choose when you ask it to work with Embedding Dimension Optimizer.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Embedding Dimension Optimizer.

  1. 01

    Find optimal dimensions

  2. 02

    Estimate impact of reduction

    Estimates impact of dimension reduction

  3. 03

    Validate task suitability

    Validates if a model is suitable for a task

Observed, not estimated

823ms average. Fast in production.

Embedding Dimension Optimizer is checked daily against the live service.

Daily averagePeak 1074ms
Aug 23Today
Fastest day
713ms
Slowest day
1074ms
14-day trend
Slowing+21%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 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 Embedding Dimension Optimizer, so you can see the experience inside your AI.

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

Embedding Dimension Optimizer Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_EVWtDbycqbTCXSEmo4nhShFkpo4qThjw3Q7LamEz/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 — Embedding Dimension Optimizer capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "embedding-dimension-optimizer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_EVWtDbycqbTCXSEmo4nhShFkpo4qThjw3Q7LamEz/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 Embedding Dimension Optimizer owners ask.

  • 01

    How does the optimizer determine the best dimension?

    The find_optimal_dimensions capability evaluates each available dimension to find the one that maximizes the quality-to-latency ratio while staying within your specified accuracyThreshold and latencyBudget.

  • 02

    Can I check if my current model is suitable for a specific task?

    Yes, you can use validate_task_suitability to check if a model configuration meets your required accuracy and latency constraints.

  • 03

    What kind of savings can I expect from dimension reduction?

    By using estimate_impact_of_reduction, you can calculate exact storage savings in bytes and the retrieval latency improvement multiplier.

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