Integrates with Azure DevOps services to enable natural language interactions for querying work items, retrieving projec...
Created byApr 22, 2025
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
Configuration
Create a .env file in the project root with the following variables:
Note: Make sure to provide the full URL to your Azure DevOps organization.
Running the Server
Usage Examples
Query Work Items
Create a Work Item
Update a Work Item
Team Management
View Project Structure
Development
The project is structured into feature modules, each implementing specific Azure DevOps capabilities:
features/work_items: Work item management functionality
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
Configuration
Create a .env file in the project root with the following variables:
Note: Make sure to provide the full URL to your Azure DevOps organization.
Running the Server
Usage Examples
Query Work Items
Create a Work Item
Update a Work Item
Team Management
View Project Structure
Development
The project is structured into feature modules, each implementing specific Azure DevOps capabilities:
features/work_items: Work item management functionality