home / mcp / azure devops mcp server
Provides a comprehensive MCP server to manage Azure DevOps work items, boards, repos, and more via a unified API.
Configuration
View docs{
"mcpServers": {
"ryancardin15-azuredevops-mcp": {
"command": "npx",
"args": [
"@ryancardin/azuredevops-mcp-server@latest"
],
"env": {
"ALLOWED_TOOLS": "listWorkItems,getWorkItemById,searchWorkItems",
"AZURE_DEVOPS_DOMAIN": "your-domain",
"AZURE_DEVOPS_ORG_URL": "https://dev.azure.com/your-organization",
"AZURE_DEVOPS_PROJECT": "your-project",
"AZURE_DEVOPS_PASSWORD": "your-password",
"AZURE_DEVOPS_USERNAME": "your-username",
"AZURE_DEVOPS_AUTH_TYPE": "pat",
"AZURE_DEVOPS_COLLECTION": "DefaultCollection",
"AZURE_DEVOPS_API_VERSION": "6.0",
"AZURE_DEVOPS_IS_ON_PREMISES": "false",
"AZURE_DEVOPS_PERSONAL_ACCESS_TOKEN": "your-personal-access-token"
}
}
}
}The Azure DevOps MCP Server provides a unified API to interact with Azure DevOps services—work items, boards, repos, projects, sprints, and more—via the Model Context Protocol. This enables AI assistants and other tools to manage and query your Azure DevOps data in a consistent, programmatic way.
You run the MCP server locally or remotely and connect your MCP client to it. Once connected, you can list, create, update, and query work items; browse boards and sprints; manage projects and iterations; work with repositories and pull requests; run tests and DevSecOps checks; handle artifacts; and leverage AI-assisted development features. Use each tool by calling its operation name and providing the required parameters. Combine multiple tools in a single workflow to automate end-to-end DevOps tasks.
Prerequisites: ensure you have Node.js installed (v16 or later) and have an Azure DevOps account with a Personal Access Token (PAT) or appropriate credentials.
npx @ryancardin/azuredevops-mcp-server@latestConfigure environment variables to connect to your Azure DevOps organization, choose authentication, and set your default project. You can tailor which tools are enabled by using the ALLOWED_TOOLS setting. You can also run the server with a local setup or as a remote service.
Key environment variables you will set include the organization URL, project, authentication type, and PAT. If you are using on-premises Azure DevOps Server, provide the collection and API version where required.
List work items using queries to retrieve items matching specific criteria.
Fetch details for a work item by its ID.
Search for work items using keywords or WIQL queries.
Retrieve work items recently updated.
Get work items assigned to you.
Create a new work item with a given type, title, and description.
Update properties of an existing work item.
Add a comment to a specific work item.
Change the state of a work item (e.g., Active, Closed).
Assign a work item to a user.
Create relationships between work items (e.g., blockers, related items).
Bulk create or update multiple work items in one operation.
List teams' boards within a project.
Retrieve columns for a specific board.
List items on a board or in a column.
Move cards between columns on a board.
Get available sprints for a project.
Fetch the current active sprint.
List work items in a specific sprint.
Retrieve capacity planning for a sprint.
Get members of a project team.
List all projects in the organization.
Get detailed information about a project.
Create a new project.
Get area paths within a project.
Get iterations for a project.
Create new area paths.
Create new iterations within a project.
Retrieve available process templates.
List work item types for a project.
Get fields for a specific work item type.
List Git repositories in a project.
Get details for a repository.
Create a new repository.
List branches in a repository.
Search code across repositories.
Browse repository contents.
Get the contents of a file in a repository.
Retrieve commit history for a repository.
List pull requests in a repository.
Create a new pull request.
Get details for a pull request.
Get comments on a pull request.
Approve a pull request.
Merge a pull request.
Run automated tests for a project or build.
Check the status of test automation.
Configure test agents for environments.
Create data generators for automated tests.
Manage test environments and configurations.
Analyze test flakiness across runs.
Identify gaps in test coverage.
Analyze impact of code changes on tests.
Access a dashboard showing test health metrics.
Optimize test selection and execution.
Create exploratory testing sessions.
Record results from exploratory testing.
Convert exploratory findings into work items.
Retrieve statistics for exploratory testing.
Obtain AI-powered code reviews.
Suggest optimizations to improve code quality.
Identify code smells in the codebase.
Predict potential bugs using historical data.
Gather metrics on developer productivity.
Estimate effort for work items and tasks.
Track trends in code quality over time.
Suggest refinements for work items.
Identify opportunities to automate repetitive tasks.
Set up intelligent alerts based on events.
Forecast potential build failures.
Optimize which tests to run for a given change.