MCP Azure DevOps Server

MCP Azure DevOps Server

What is MCP Azure DevOps Server about?

MCP Azure DevOps Server bridges natural‑language AI assistants with Azure DevOps, allowing tasks such as querying, creating, updating work items, and retrieving project or team information through conversational prompts.

How to use MCP Azure DevOps Server?

1. Clone the repository and install dependencies:

   git clone https://github.com/Vortiago/mcp-azure-devops.git
   cd mcp-azure-devops
   uv pip install -e ".[dev]"
   

2. Configure credentials by creating a .env file with your Azure DevOps PAT and organization URL:

   AZURE_DEVOPS_PAT=your_personal_access_token
   AZURE_DEVOPS_ORGANIZATION_URL=https://dev.azure.com/your-organisation
   

3. Run the server in development mode:

   mcp dev src/mcp_azure_devops/server.py
   

4. Install in Claude Desktop (or any MCP‑compatible client):

   mcp install src/mcp_azure_devops/server.py --name "Azure DevOps Assistant"
   

5. Interact with the assistant using natural‑language commands (e.g., “Show me all active bugs assigned to me in the current sprint”).

Key features of MCP Azure DevOps Server

• Work Item Management: query, create, update, comment, and manage parent‑child relationships.
• Project Management: list projects, teams, team members, area paths, and iterations.
• Planned Extensions: pipeline status, pull‑request handling, sprint planning, branch policy administration.

Use cases of MCP Azure DevOps Server

• Developers ask an AI assistant to create or update work items without leaving the chat interface.
• Project managers retrieve sprint metrics, team rosters, or iteration schedules via simple queries.
• QA engineers add comments or change bug statuses directly through natural language commands.
• Automation scripts invoke the server to synchronize Azure DevOps data with other systems.

FAQ from the MCP Azure DevOps Server

Q: Which Azure DevOps permissions are required? A: A Personal Access Token with scopes for Work Items, Project and Team read/write access.

Q: Can I run the server in production? A: Yes, deploy the same server.py script in any environment that supports Python 3.10+ and set the required environment variables.

Q: Is there support for pipelines and pull requests? A: Those features are planned for future releases.

Q: How do I add new capabilities? A: Extend the features/ modules and update the MCP manifest; contributions are welcomed via pull requests.

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

• Built with MCP Python SDK
• Uses Azure DevOps Python API