【MCP Server】Azure DevOps × Claude Desktop 連携ガイド | AI でデータを徹底活用
Model Context Protocol (MCP) is an emerging, open-source standard for connecting LLMs with external services and data sources. Through MCP Servers, AI clients can perform actions like opening Jira tickets, posting Slack messages, committing GitHub branches and more. With CData MCP Servers, these capabilities expand exponentially.
In this article, we guide the reader through installing the CData MCP Server for Azure DevOps, configuring the connection to Azure DevOps, and asking questions of the data in Claude Desktop.
Prerequisites
You need to download Claude Desktop (download) and create an account before continuing.
Overview
Here's a quick overview of the steps:
- Download and install the CData MCP Server for Azure DevOps
- Configure the connection to Azure DevOps
- Ask questions about the data in Claude Desktop
Step 1: Download and install the CData MCP Server
- To begin, navigate to https://www.cdata.com/solutions/mcp/connectors and download the CData MCP Server for Azure DevOps.
- Find and double-click the installer to begin the installation.
- Follow the prompts to complete the installation.
When the installation is complete, you are ready to configure your MCP Server by connecting to Azure DevOps.
Step 2: Configure the connection to Azure DevOps
- After installation, the CData MCP Server configuration wizard should open automatically.
NOTE: If the wizard does not open automatically, search for "CData MCP Server" in the Windows search bar and double-click the application.

- Click the dropdown menu in MCP Configuration > Configuration Name and select "
"
- Name the configuration (e.g. "cdataazuredevops") and click "OK."
NOTE: This name is used as the name for the MCP server and as the prefix for all of the MCP Server's tools.
Connecting to Azure DevOps
AzureDevOps 接続プロパティの取得・設定方法
Azure DevOps アカウントに接続するには、Profile -> Organizations に移動し、アカウントの組織名を取得します。Organization プロパティをこの値に設定します。
Note: 複数のカタログやスキーマに存在するテーブル名もあります。テーブルをクエリする際は、Catalog およびSchema 接続プロパティ、または完全修飾テーブル名のいずれかでカタログとスキーマを指定する必要があります。
Azure DevOps への認証
Azure DevOps は、Basic 認証とAzure AD(OAuth ベース)認証の両方をサポートします。
Basic
Basic 認証でAzure DevOps に接続する場合、Organization とPersonalAccessToken の両方を指定します。 パーソナルアクセストークンを生成するには、Azure DevOps 組織アカウントにログインし、Profile -> Personal Access Tokens -> New Token に移動します。生成されたトークンが表示されます。
Azure AD
Azure AD は、Microsoft のマルチテナント、クラウドベースのディレクトリおよびID 管理サービスです。 これはユーザーベースの認証で、AuthScheme をAzureAD に設定し、Organization をAzure DevOps Organization の名前に設定する必要があります。 Web アプリケーションを介したAzure AD への認証には、必ずカスタムOAuth アプリケーションの作成が必要です。 詳しい認証方法は、ヘルプドキュメント の「Azure DevOps への認証」セクションを参照してください。
Enter the appropriate connection properties in the configuration wizard.
- Click "Connect" to authenticate with Azure DevOps through OAuth.
NOTE: The configuration wizard should open your browser and ask you to sign into Azure DevOps. If your browser does not open, close the configuration wizard and re-open the application using "Run as Administrator" (see below).
- Finally, click "Save Configuration" to save the MCP server.
NOTE: This saves the configuration details to a separate file and updates the Claude Desktop configuration file (claude_desktop_config.json) to start the CData MCP Server when the Claude Desktop client starts.
With the CData MCP Server configured, you are ready to start asking questions of your live data from Claude.
Step 3: Ask AI for answers from live Azure DevOps のデータ
Now that we have installed the CData MCP Server and configured a connection, we are ready to start with Azure DevOps のデータ in Claude Desktop.
- Open Claude Desktop. It may take a moment for the MCP Servers to start, but you will see the list of servers and tools available in the Claude interface (look for the settings icon below the prompt bar).
You can individually enable and disable specific tools by clicking on the server name.
- Now that you have connected, you can ask Claude questions about the Azure DevOps のデータ. For example: "Can you give me a quantitative analysis about my closed-won opportunities by industry?"
NOTE: Claude may need to explore the Azure DevOps のデータ to make sense of it before it can begin answering questions of the data. The tabular model presented by CData alongside the database tools available simplify the data exploration and analysis for an LLM.
Connect your AI to your data today!
CData MCP Servers make it easier than ever for LLMs to work with live enterprise data. To explore the technology hands-on, download a free, 30-day trial or visit the CData Community to share insights, ask questions, and help shape the future of enterprise-ready AI.