• CONTEXT
  • ACCURACY
  • RELEVANCE
  • HUMAN

How to perform semantic vector searches with your AI

Connect your Azure index to your AI client to move beyond keyword matching. Your agent starts understanding the intent behind your questions.

Ask AI about this page

Short answer

How can I make my AI search by meaning rather than keywords?

You connect your Azure Cognitive Search index to your AI client to enable vector-based retrieval. This allows your agent to find documents based on conceptual similarity, even if the exact words don't match. You'll see how the AI pulls relevant context through the following steps.

The outcomes

Where your search results land

The AI uses your index to provide context for its answers.

CONTEXT

Meaningful document retrieval

The AI uses vector similarity to find the right files. It pulls data that matches the concept of your query, not just the spelling.

ACCURACY

Reduced hallucination

By grounding the agent in your specific Azure index, it relies on your actual data. This keeps the answers tied to your documents.

RELEVANCE

Better query results

Your agent identifies the intent behind a question. It finds the most relevant pieces of information to build a response.

HUMAN

Manual index management

The AI cannot create or modify your Azure index. You still need to manage your data ingestion and vectorization in Azure.

The workflow

What your AI does when a query arrives.

The AI handles the heavy lifting of finding and reading your data.

  1. Identify the index

    The AI looks up your specific Azure search index to understand what data is available for the task.

    get_index

  2. Find similar content

    The agent performs a mathematical search to find documents that are conceptually close to your question.

    vector_search

  3. Retrieve context

    The AI pulls the most relevant text chunks from the index to use as a reference.

    vector_search

  4. Synthesize answer

    The agent reads the retrieved data and writes a response based on those specific findings.

    vector_search

Try it

Copy these to start.

Use these prompts once your Azure Cognitive Search is connected.

Starting points

Swap the bracketed text for your actual index names or specific topics.

Azure Cognitive Search Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/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 Cognitive Search capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "azure-cognitive-search-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_hdKYLP4Ky0e0ym1FqqZkykLxQEDMxyTOrt4HuJb3/mcp"
    }
  }
}
Copy into chat04

  • Search my [index_name] for documents about our Q3 marketing strategy.

  • Based on the [index_name] index, what are our current safety protocols?

  • Find any technical manuals in [index_name] that mention hydraulic pressure.

  • Summarize the main themes found in the [index_name] dataset.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Azure Cognitive Search once, then ask.

Follow the single link to authorize the connection. Your credentials stay encrypted, and you can immediately start chatting with your data.

Connect Azure Cognitive Search to your AI

FAQ

How this task behaves

  • 01

    Can the AI add new documents to my Azure index?

    No. The AI can only read from your index using the provided tools. You must upload or update documents through Azure directly.

  • 02

    Does the AI see all my data at once?

    No. The AI only retrieves the specific document chunks that are mathematically similar to your current question.

  • 03

    What if my search returns no results?

    If the vector search finds no close matches in your index, the AI will tell you it couldn't find relevant information.

  • 04

    Can the AI delete files from my index?

    No. This MCP is read-only. It has no capability to delete or modify your data.

  • 05

    Do I need to create embeddings myself?

    The AI uses the vector search tool to interact with your existing index, so your index must already be configured for vector search in Azure.

  • More questions about Azure Cognitive Search? The Connector page answers them. See everything the Azure Cognitive Search Connector can do

Connect Azure Cognitive Search to Claude, Cursor, ChatGPT & more