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MCP Server
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MCP Server

This project provides two implementations of the MCP server, connecting Claude Desktop with Azure search capabilities, supporting document search and web search. You can choose to use the Azure AI Agent service or directly integrate Azure AI Search.
Search toolsKnowledge management and memory#Azure Search#AI Agent#Document retrieval#Web search.Python
2 points
9.3K
Open Site

Overview

Installation

Content Details

Alternatives

What is the Azure AI MCP server?

This is a bridge that connects Claude Desktop with Azure AI services, allowing you to directly search your document content or Internet information in Claude. There are two implementation methods: it is recommended to use Azure AI Agent Service (including document and web search), or directly connect to the Azure AI Search service.

How to use the Azure AI MCP server?

You need to configure Azure resources first, then select an implementation method (Agent Service or direct search), and finally configure the MCP server connection in Claude Desktop.

Applicable scenarios

This service is particularly useful when you need to let Claude access your private documents or obtain the latest network information. It is suitable for scenarios such as research, data analysis, and knowledge management.

Main features

Azure AI Agent service
Provides intelligent optimized document search and web search functions, and the results are enhanced by AI
Direct Azure AI search
Provides three ways of keyword search, vector search, and hybrid search to directly access your index data
Source citation
Web search results include reference information of the original source
Advantages
AI-enhanced search results are more accurate and relevant
Can search private documents and the public Internet simultaneously
Flexible configuration options meet different needs
Seamlessly integrates with the Claude Desktop interface
Limitations
Requires an Azure subscription and relevant resources
The initial configuration has a certain technical threshold
Web search depends on the Bing service

How to use

Prepare Azure resources
Create an AI search service and index in the Azure portal (for the direct search method), or create an AI project and configure the connection (for the Agent Service method)
Set up the project environment
Create a project directory, set up the.env configuration file, and install the Python virtual environment and dependent packages
Configure Claude Desktop
Add MCP server settings to the Claude configuration file, specifying the Python path and the script file
Test the connection
Restart Claude Desktop, find the MCP tool icon (hammer icon) in the lower right corner of the input box, and try to search

Usage examples

Research support
Quickly find relevant documents and the latest Internet information when writing a research report
Knowledge management
Quickly find information on a specific topic from the enterprise knowledge base

Frequently Asked Questions

Why doesn't the MCP server appear in Claude?
What's the difference between the two implementation methods?
What if the search results are inaccurate?

Related resources

Get started with Azure AI Search
Official getting-started guide for the Azure AI Search service
Quickstart for Azure AI Agent
Configuration guide for the Azure AI Agent service

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "azure-ai-agent": {
      "command": "C:\\path\\to\\.venv\\Scripts\\python.exe",
      "args": ["C:\\path\\to\\azure_ai_agent_service_server.py"],
      "env": {
        "PROJECT_CONNECTION_STRING": "your-project-connection-string",
        "MODEL_DEPLOYMENT_NAME": "your-model-deployment-name",
        "AI_SEARCH_CONNECTION_NAME": "your-search-connection-name",
        "BING_CONNECTION_NAME": "your-bing-connection-name",
        "AI_SEARCH_INDEX_NAME": "your-index-name"
      }
    }
  }
}

{
     "mcpServers": {
       "azure-search": {
         "command": "C:\\path\\to\\.venv\\Scripts\\python.exe",
         "args": ["C:\\path\\to\\azure_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: Your key is sensitive information, do not share it with anyone.

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