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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Embedding Similarity Calculator with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Calculate mathematical distances and similarity scores between multidimensional numerical vectors.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Observed, not estimated

595ms average. Fast in production.

Embedding Similarity Calculator is checked daily against the live service.

Daily averagePeak 817ms
Aug 21Today
Fastest day
471ms
Slowest day
817ms
14-day trend
Improving-6%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 0 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 Similarity Calculator, so you can see the experience inside your AI.

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

Embedding Similarity Calculator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_Jw1zV0EdxZijh9ns0Ve4DwNFVTYvTKlOlQyDwkeV/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 Similarity Calculator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "embedding-similarity-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_Jw1zV0EdxZijh9ns0Ve4DwNFVTYvTKlOlQyDwkeV/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 Similarity Calculator owners ask.

  • 01

    What metrics are supported?

    The calculator supports Cosine Similarity, Euclidean Distance, Dot Product Similarity, and Manhattan Distance. Capabilities available: your_tool_name.

  • 02

    Do all vectors need to have the same size?

    Yes, for any mathematical comparison to be valid, all vectors involved must share the exact same dimensionality.

  • 03

    How does ranking work for distance metrics?

    For distance-based metrics like Euclidean and Manhattan, vectors with smaller values are ranked higher. For similarity-based metrics like Cosine and Dot Product, larger values are ranked higher.

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