How to Use the Azure Cognitive Search MCP in Cursor

Query Azure Cognitive Search indexes directly in Cursor to write code against real production schemas.

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Connect Azure Cognitive Search MCP to Cursor

Create your Vinkius account to connect Azure Cognitive Search to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Azure Cognitive Search with Cursor

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Generate Code in Cursor with Live Azure Search Indexes

`get_index` retrieves your exact Azure schema definitions directly into your active Cursor editor. Your Cursor agent reads the actual field names and data types, eliminating the need to guess schema structures while writing search integration code. Instead of coding against outdated documentation, `list_indexes` shows you every active Azure index in your environment. Cursor uses this live context to generate accurate search integration code on your first try.

Test Lexical and Vector Queries in Cursor Agent Mode

`search_documents` executes lexical search queries against your live Azure indexes directly from the Cursor chat sidebar. You can verify that your Azure query syntax is correct before committing the code to your repository. For semantic search implementations, `vector_search` runs KNN vector queries against your Azure embedding profiles. Cursor displays the raw JSON results so you can tune your Azure vector search parameters in real time.

Validate Indexer Pipelines and Fetch Document Payload Keys

`list_indexers` exposes the scheduled run states of your Azure data ingestion pipelines. When debugging search sync issues in your application, Cursor checks these run states to confirm if an indexer is lagging. `get_document` retrieves a single Azure document by its UUID key so you can inspect the exact payload structure. This ensures your application's data parsing logic matches the actual document structure returned by Azure in Cursor.

Setup guide

Set up Azure Cognitive Search MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the Azure Cognitive Search MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent Azure Cognitive Search transactions." If the MCP tools are loaded correctly, Cursor will call the Azure Cognitive Search tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "azure-cognitive-search-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Azure Cognitive Search. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Azure Cognitive Search MCP in Cursor

Add the MCP Server configuration to your project's local settings file. Cursor automatically loads the tools, allowing you to query your indexes directly from the editor's Agent mode.

Yes, Cursor uses the search tools to execute real test queries. This allows the editor to validate query structures and generate precise API calls based on actual search results.

It does. The vector tools let Cursor run KNN queries against your Azure embedding profiles, helping you write and test vector search code without leaving the editor.

You can configure it globally in your user-level configuration file. This makes the search tools available across all your workspaces without needing a local config file in every repository.

Your Azure API keys are stored locally on your machine and are only used to authenticate requests. The Vinkius MCP Server sandbox ensures that your Azure index schema definitions and document payloads are never cached or exposed to third parties.

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