# mcp-azure-devops

> MCP Server

This repository hosts an MCP server that bridges AI assistants with Azure DevOps, enabling natural language interaction for work item queries. Planned features include pipeline operations and pull request handling.

## Overview

- **Category:** Developer Tools
- **Language:** Python
- **Stars:** 79
- **Forks:** 4
- **Owner:** Vortiago
- **GitHub:** https://github.com/Vortiago/mcp-azure-devops
- **Created:** 2025-03-13T18:14:14+00:00
- **Updated:** 2025-03-28T15:30:03+00:00
- **Source:** https://model-context-protocol.com/servers/ai-azure-devops-interaction-mcp-server

## Setup

## Setup

1.  Prerequisites:
    - Python 3.9+
    - Azure DevOps account with appropriate permissions
    - Personal Access Token (PAT) with necessary scopes for Azure DevOps API access
2.  Installation:
    ```bash
    # Clone the repository
    git clone https://github.com/your-username/mcp-azure-devops.git
    cd mcp-azure-devops

    # Install in development mode
    pip install -e ".[dev]"

    # Install from PyPi
    pip install mcp_azure_devops
    ```
3.  Configuration:
    - Create a `.env` file in the project root with the following variables:
    ```
    AZURE_DEVOPS_PAT=your_personal_access_token
    AZURE_DEVOPS_ORGANIZATION_URL=https://your-organization.visualstudio.com or https://dev.azure.com/your-organisation
    ```
    - Note: Make sure to provide the full URL to your Azure DevOps organization.
4.  Running the Server:
    ```bash
    # Development mode with the MCP Inspector
    mcp dev src/mcp_azure_devops/server.py

    # Install in Claude Desktop
    mcp install src/mcp_azure_devops/server.py --name "Azure DevOps Assistant"
    ```

## Tools

## Available Tools

1.  Work Item Management (Query work items using WIQL)
2.  Work Item Management (Create and update work items - Planned)
3.  Pipeline Operations (Query pipeline status and trigger new pipeline runs - Planned)
4.  Pull Request Handling (Create, update, and review Pull Requests - Planned)
5.  Sprint Management (Plan and manage sprints and iterations - Planned)
6.  Branch Policy Administration (Configure and manage branch policies - Planned)