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Use Azure AI Search with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Execute RAG queries against Azure AI Search natively. search vectors, full-text documents, and audit cloud indexes directly from your AI agent.

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 · 6 capabilities

The complete Azure AI Search capability set.

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

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through Azure AI Search.

  1. 01

    List indexes

    List all Azure AI Search indexes

  2. 02

    Get index

    Get explicit details of a single Azure search index configuration

  3. 03

    List datasources

    List Azure AI Search data sources explicitly mapped

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through Azure AI Search.

  1. 04

    List indexers

    List explicit scheduled Azure indexer tasks

  2. 05

    Search documents

    Execute lexical Full-Text search queries against Azure Indexes

  3. 06

    Vector search

    Highly targeted relevance extraction spanning dimensional maps. Perform Azure vector similarity searches via explicit embedding spaces

Observed, not estimated

819ms average. Fast in production.

Azure AI Search is checked daily against the live service.

Daily averagePeak 1058ms
Aug 24Today
Fastest day
680ms
Slowest day
1058ms
14-day trend
Stable-2%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 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 Azure AI Search, so you can see the experience inside your AI.

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

Azure AI Search Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_UGnljcexY2MC0gUzqrUAvXNWXI0LuEzLwo7dKO1k/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 — Azure AI Search capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "azure-ai-search-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_UGnljcexY2MC0gUzqrUAvXNWXI0LuEzLwo7dKO1k/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 Azure AI Search owners ask.

  • 01

    Can my AI use this to query documents using vector embeddings directly?

    Yes. If your agent is equipped with an embedding capability (like an OpenAI Ada dimension generator), it can compute the embedding float locally and transmit the precise K-Nearest Neighbors request into your Azure Index via the vector_search capability to return perfectly isolated contextual passages.

  • 02

    How can I verify if my Azure Search Indexer completed successfully?

    You can ask your agent to list all indexers. It retrieves the scheduled background configurations defining how your Azure SQL or Blob stores migrate into Search form, allowing you to instantly assess if the pipeline is active or encountering extraction errors.

  • 03

    Can I audit the core configuration components of a specific index?

    Absolutely. By providing the exact Index name, your AI fetches the exhaustive schema architecture: semantic mapping references, exact lexical BM25 fallback values, field weights, language analyzers, and HNSW graphs mapping vector space limits.

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