Azure AI Search MCP Server: Enterprise AI & Real-Time Insights

Key Features of Azure AI Search MCP Server

Use Cases for Real-Time AI Insights

Azure AI Search MCP Server

A Model Context Protocol (MCP) server that integrates with Azure AI Search, enabling Claude Desktop to query your search indexes using keyword, vector, or hybrid methods.

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Overview

This project provides an MCP server implementation that connects Claude Desktop with Azure AI Search. The server supports three search methods:

• Keyword Search: Exact lexical matches.
• Vector Search: Semantic similarity using vector embeddings.
• Hybrid Search: A combination of keyword and vector searches.

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Features

• Seamless Integration: Connect Claude Desktop with Azure AI Search.
• Multiple Search Methods: Supports keyword, vector, and hybrid searches.
• Customizable: Easy to extend with additional tools or modify search logic.

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Requirements

• Python: Version 3.10 or higher
• Azure AI Search Service: Configured with an index containing vectorized text data
• Claude Desktop: Latest version
• Operating System: Windows or macOS (instructions provided for Windows, but adaptable)

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Quick Start Guide

1. Installation

1. Set Up Project Directory:

   mkdir mcp-server-azure-ai-search

cd mcp-server-azure-ai-search

2. Create a.env File:

   echo "AZURE_SEARCH_SERVICE_ENDPOINT=https://your-service-name.search.windows.net" > .env

echo "AZURE_SEARCH_INDEX_NAME=your-index-name" >> .env
echo "AZURE_SEARCH_API_KEY=your-api-key" >> .env

2. Set Up Virtual Environment

1. Create and Activate the Virtual Environment:

   uv venv

.venv\Scripts\activate

2. Install Dependencies:

   uv pip install "mcp[cli]" azure-search-documents==11.5.2 azure-identity python-dotenv

3. Server Script

Create a file named azure_search_server.py. This script:

• Loads configuration from the .env file.
• Initializes the Azure AI Search client.
• Defines search functions for keyword, vector, and hybrid searches.
• Registers these functions as MCP tools for Claude Desktop.

For detailed implementation, refer to the inline comments within the script.

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Configuring Claude Desktop

1. Open Claude Desktop.

2. Navigate to Settings > Developer > Edit Config.

3. Add the following configuration (update paths and credentials):

   {
   "mcpServers": {
   "azure-search": {
   "command": "C:path\tomcp-server-azure-ai-search.venvScriptspython.exe",
   "args": ["C:path\tomcp-server-azure-ai-searchazure_search_server.py"],
   "env": {
   "AZURE_SEARCH_SERVICE_ENDPOINT": "https://your-service-name.search.windows.net",
   "AZURE_SEARCH_INDEX_NAME": "your-index-name",
   "AZURE_SEARCH_API_KEY": "your-api-key"
   }
   }
   }

}

Note: Replace C:\path\to\mcp-server-azure-ai-search with your actual project path.

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Testing the Server

1. Restart Claude Desktop to load the new configuration.
2. Look for the MCP tools icon (hammer icon) in the bottom-right of the input field.
3. Try queries such as:
   * "Can you search for information about AI in my Azure Search index?"
   * "Search for vector databases using the vector search tool."
   * "Find information about neural networks using hybrid search."

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Troubleshooting

• Server Not Appearing:
  • Check Claude Desktop logs (typically found at %APPDATA%\Claude\logs\mcp*.log on Windows).
  • Verify file paths and environment variables in the configuration.
  • Test running the server directly via python azure_search_server.py. or uv run python azure_search_server.py

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Customizing Your Server

• Modify Search Logic: Adjust the search methods in the AzureSearchClient class.
• Add New Tools: Use the @mcp.tool() decorator to integrate additional search functionalities.
• Customize Output: Edit the markdown formatting function for search results.

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License

This project is licensed under the MIT License.