Azure DevOps MCP Server
@aymenfurter
Azure DevOps MCP Server について
概要はまだありません
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"ado-mcp-server-python": {
"command": "docker",
"args": [
"build",
"-t",
"ado-mcp-server",
"."
]
}
}
}ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is Azure DevOps MCP Server?
Azure DevOps MCP Server is a Model Context Protocol (MCP) server that provides work item management capabilities for Azure DevOps. It is intended for developers who want to integrate AI assistants with Azure DevOps using a Docker container and a Personal Access Token.
How to use Azure DevOps MCP Server?
Build the Docker image with docker build -t ado-mcp-server . then run the container with three environment variables: ADO_PERSONAL_ACCESS_TOKEN, ADO_ORGANIZATION_URL, and ADO_PROJECT_NAME. For VS Code integration, add the provided JSON configuration to your editor settings.
Key features of Azure DevOps MCP Server
- Search existing work items
- Create new work items
- Update existing work items
- Retrieve work item states
- Simple command-line interface for testing
Use cases of Azure DevOps MCP Server
- Querying work items from an AI chat assistant
- Automatically creating work items based on user requests
- Updating work item status or fields via natural language
- Getting an overview of work item states in a project
FAQ from Azure DevOps MCP Server
What are the prerequisites to use this server?
Docker, an Azure DevOps Personal Access Token with appropriate permissions, and the organization URL and project name.
How do I integrate it with VS Code?
Add the provided JSON configuration block to your VS Code settings, using docker as the command and passing the required environment variables through prompts.
What operations does the server support?
It supports searching, creating, updating work items, and getting work item states.
What environment variables must be set?
ADO_PERSONAL_ACCESS_TOKEN, ADO_ORGANIZATION_URL, and ADO_PROJECT_NAME.
How can I run tests for the server?
Use docker run with the same environment variables and append python -m pytest as the command.
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