Cover image
Try Now
2025-04-10

Ein MCP -Server (Modellkontextprotokoll), mit dem AI -Assistenten über Python SDK mit Azure DevOps Services interagieren können.

3 years

Works with Finder

2

Github Watches

12

Github Forks

23

Github Stars

MCP Azure DevOps Server

A Model Context Protocol (MCP) server enabling AI assistants to interact with Azure DevOps services.

Overview

This project implements a Model Context Protocol (MCP) server that allows AI assistants (like Claude) to interact with Azure DevOps, providing a bridge between natural language interactions and the Azure DevOps REST API.

Features

Currently implemented:

Work Item Management

  • Query Work Items: Search for work items using WIQL queries
  • Get Work Item Details: View complete work item information
  • Create Work Items: Add new tasks, bugs, user stories, and other work item types
  • Update Work Items: Modify existing work items' fields and properties
  • Add Comments: Post comments on work items
  • View Comments: Retrieve the comment history for a work item
  • Parent-Child Relationships: Establish hierarchy between work items

Project Management

  • Get Projects: View all accessible projects in the organization
  • Get Teams: List all teams within the organization
  • Team Members: View team membership information
  • Team Area Paths: Retrieve area paths assigned to teams
  • Team Iterations: Access team iteration/sprint configurations

Planned features:

  • Pipeline Operations: Query pipeline status and trigger new pipeline runs
  • Pull Request Handling: Create, update, and review Pull Requests
  • Sprint Management: Plan and manage sprints and iterations
  • Branch Policy Administration: Configure and manage branch policies

Getting Started

Prerequisites

  • Python 3.10+
  • Azure DevOps account with appropriate permissions
  • Personal Access Token (PAT) with necessary scopes for Azure DevOps API access

Installation

# Clone the repository
git clone https://github.com/Vortiago/mcp-azure-devops.git
cd mcp-azure-devops

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

# Install from PyPi
pip install mcp-azure-devops

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.

Running the Server

# 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"

Usage Examples

Query Work Items

Show me all active bugs assigned to me in the current sprint

Create a Work Item

Create a user story in the ProjectX with the title "Implement user authentication" and assign it to john.doe@example.com

Update a Work Item

Change the status of bug #1234 to "Resolved" and add a comment explaining the fix

Team Management

Show me all the team members in the "Core Development" team in the "ProjectX" project

View Project Structure

List all projects in my organization and show me the iterations for the Development team

Development

The project is structured into feature modules, each implementing specific Azure DevOps capabilities:

  • features/work_items: Work item management functionality
  • features/projects: Project management capabilities
  • features/teams: Team management features
  • utils: Common utilities and client initialization

For more information on development, see the CLAUDE.md file.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

相关推荐

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • https://maiplestudio.com
  • Find Exhibitors, Speakers and more

  • lumpenspace
  • Take an adjectivised noun, and create images making it progressively more adjective!

  • https://appia.in
  • Siri Shortcut Finder – your go-to place for discovering amazing Siri Shortcuts with ease

  • Carlos Ferrin
  • Encuentra películas y series en plataformas de streaming.

  • Yusuf Emre Yeşilyurt
  • I find academic articles and books for research and literature reviews.

  • tomoyoshi hirata
  • Sony α7IIIマニュアルアシスタント

  • apappascs
  • Entdecken Sie die umfassendste und aktuellste Sammlung von MCP-Servern auf dem Markt. Dieses Repository dient als zentraler Hub und bietet einen umfangreichen Katalog von Open-Source- und Proprietary MCP-Servern mit Funktionen, Dokumentationslinks und Mitwirkenden.

  • jae-jae
  • MCP -Server für den Fetch -Webseiteninhalt mit dem Headless -Browser von Dramatikern.

  • ravitemer
  • Ein leistungsstarkes Neovim -Plugin für die Verwaltung von MCP -Servern (Modellkontextprotokoll)

  • patruff
  • Brücke zwischen Ollama und MCP -Servern und ermöglicht es lokalen LLMs, Modellkontextprotokoll -Tools zu verwenden

  • pontusab
  • Die Cursor & Windsurf -Community finden Regeln und MCPs

  • av
  • Führen Sie mühelos LLM -Backends, APIs, Frontends und Dienste mit einem Befehl aus.

  • WangRongsheng
  • 🧑‍🚀 全世界最好的 llm 资料总结(数据处理、模型训练、模型部署、 O1 模型、 MCP 、小语言模型、视觉语言模型) | Zusammenfassung der weltbesten LLM -Ressourcen.

  • Mintplex-Labs
  • Die All-in-One-Desktop & Docker-AI-Anwendung mit integriertem Lappen, AI-Agenten, No-Code-Agent Builder, MCP-Kompatibilität und vielem mehr.

  • appcypher
  • Awesome MCP -Server - eine kuratierte Liste von Modellkontext -Protokollservern für Modellkontext

    Reviews

    5 (1)
    Avatar
    user_TAjw2wAS
    2025-04-17

    As a devoted user of mcp-azure-devops, I’m thoroughly impressed with its seamless integration and functionality. Vortiago has done an excellent job creating a tool that simplifies Azure DevOps tasks and enhances productivity. It's user-friendly and efficient, making my workflow smoother. Highly recommend it to anyone looking to optimize their DevOps processes!