Azure DevOps MCP Server
Standardized AI access to Azure DevOps via Model Context Protocol.
Key Features
Use Cases
README
ℹ️ DISCUSSION: Microsoft launched an official ADO MCP Server! 🎉🎉🎉
Azure DevOps MCP Server
A Model Context Protocol (MCP) server implementation for Azure DevOps, allowing AI assistants to interact with Azure DevOps APIs through a standardized protocol.
Overview
This server implements the Model Context Protocol (MCP) for Azure DevOps, enabling AI assistants like Claude to interact with Azure DevOps resources securely. The server acts as a bridge between AI models and Azure DevOps APIs, providing a standardized way to:
- Access and manage projects, work items, repositories, and more
- Create and update work items, branches, and pull requests
- Execute common DevOps workflows through natural language
- Access repository content via standardized resource URIs
- Safely authenticate and interact with Azure DevOps resources
Server Structure
The server is structured around the Model Context Protocol (MCP) for communicating with AI assistants. It provides tools for interacting with Azure DevOps resources including:
- Projects
- Work Items
- Repositories
- Pull Requests
- Branches
- Pipelines
Core Components
- AzureDevOpsServer: Main server class that initializes the MCP server and registers tools
- Feature Modules: Organized by feature area (work-items, projects, repositories, etc.)
- Request Handlers: Each feature module provides request identification and handling functions
- Tool Handlers: Modular functions for each Azure DevOps operation
- Configuration: Environment-based configuration for organization URL, PAT, etc.
The server uses a feature-based architecture where each feature area (like work-items, projects, repositories) is encapsulated in its own module. This makes the codebase more maintainable and easier to extend with new features.
Getting Started
Prerequisites
- Node.js (v16+)
- npm or yarn
- Azure DevOps account with appropriate access
- Authentication credentials (see Authentication Guide for details):
- Personal Access Token (PAT), or
- Azure Identity credentials, or
- Azure CLI login
Running with NPX
Usage with Claude Desktop/Cursor AI
To integrate with Claude Desktop or Cursor AI, add one of the following configurations to your configuration file.
Azure Identity Authentication
Be sure you are logged in to Azure CLI with az login then add the following:
{
"mcpServers": {
"azureDevOps": {
"command": "npx",
"args": ["-y", "@tiberriver256/mcp-server-azure-devops"],
"env": {
"AZURE_DEVOPS_ORG_URL": "https://dev.azure.com/your-organization",
"AZURE_DEVOPS_AUTH_METHOD": "azure-identity",
"AZURE_DEVOPS_DEFAULT_PROJECT": "your-project-name"
}
}
}
}
Personal Access Token (PAT) Authentication
{
"mcpServers": {
"azureDevOps": {
"command": "npx",
"args": ["-y", "@tiberriver256/mcp-server-azure-devops"],
"env": {
"AZURE_DEVOPS_ORG_URL": "https://dev.azure.com/your-organization",
"AZURE_DEVOPS_AUTH_METHOD": "pat",
"AZURE_DEVOPS_PAT": "<YOUR_PAT>",
"AZURE_DEVOPS_DEFAULT_PROJECT": "your-project-name"
}
}
}
}
For detailed configuration instructions and more authentication options, see the Authentication Guide.
Authentication Methods
This server supports multiple authentication methods for connecting to Azure DevOps APIs. For detailed setup instructions, configuration examples, and troubleshooting tips, see the Authentication Guide.
Supported Authentication Methods
- Personal Access Token (PAT) - Simple token-based authentication
- Azure Identity (DefaultAzureCredential) - Flexible authentication using the Azure Identity SDK
- Azure CLI - Authentication using your Azure CLI login
Example configuration files for each authentication method are available in the examples directory.
Environment Variables
For a complete list of environment variables and their descriptions, see the Authentication Guide.
Key environment variables include:
| Variable | Description | Required | Default |
|---|---|---|---|
AZURE_DEVOPS_AUTH_METHOD |
Authentication method (pat, azure-identity, or azure-cli) - case-insensitive |
No | azure-identity |
AZURE_DEVOPS_ORG_URL |
Full URL to your Azure DevOps organization | Yes | - |
AZURE_DEVOPS_PAT |
Personal Access Token (for PAT auth) | Only with PAT auth | - |
AZURE_DEVOPS_DEFAULT_PROJECT |
Default project if none specified | No | - |
AZURE_DEVOPS_API_VERSION |
API version to use | No | Latest |
AZURE_TENANT_ID |
Azure AD tenant ID (for service principals) | Only with service principals | - |
AZURE_CLIENT_ID |
Azure AD application ID (for service principals) | Only with service principals | - |
AZURE_CLIENT_SECRET |
Azure AD client secret (for service principals) | Only with service principals | - |
LOG_LEVEL |
Logging level (debug, info, warn, error) | No | info |
Troubleshooting Authentication
For detailed troubleshooting information for each authentication method, see the Authentication Guide.
Common issues include:
- Invalid or expired credentials
- Insufficient permissions
- Network connectivity problems
- Configuration errors
Authentication Implementation Details
For technical details about how authentication is implemented in the Azure DevOps MCP server, see the Authentication Guide and the source code in the src/auth directory.
Available Tools
The Azure DevOps MCP server provides a variety of tools for interacting with Azure DevOps resources. For detailed documentation on each tool, please refer to the corresponding documentation.
User Tools
get_me: Get details of the authenticated user (id, displayName, email)
Organization Tools
list_organizations: List all accessible organizations
Project Tools
list_projects: List all projects in an organizationget_project: Get details of a specific projectget_project_details: Get comprehensive details of a project including process, work item types, and teams
Repository Tools
list_repositories: List all repositories in a projectget_repository: Get details of a specific repositoryget_repository_details: Get detailed information about a repository including statistics and refsget_file_content: Get content of a file or directory from a repository
Work Item Tools
get_work_item: Retrieve a work item by IDcreate_work_item: Create a new work itemupdate_work_item: Update an existing work itemlist_work_items: List work items in a projectmanage_work_item_link: Add, remove, or update links between work items
Search Tools
search_code: Search for code across repositories in a projectsearch_wiki: Search for content across wiki pages in a projectsearch_work_items: Search for work items across projects in Azure DevOps
Pipelines Tools
list_pipelines: List pipelines in a projectget_pipeline: Get details of a specific pipelinetrigger_pipeline: Trigger a pipeline run with customizable parameters
Wiki Tools
get_wikis: List all wikis in a projectget_wiki_page: Get content of a specific wiki page as plain text
Pull Request Tools
create_pull_request- Create a new pull requestlist_pull_requests- List pull requests in a repositoryadd_pull_request_comment- Add a comment to a pull requestget_pull_request_comments- Get comments from a pull requestupdate_pull_request- Update an existing pull request (title, description, status, draft state, reviewers, work items)
For comprehensive documentation on all tools, see the Tools Documentation.
Contributing
Contributions are welcome! Please see CONTRIBUTING.md for contribution guidelines.
Star History
License
MIT
Star History
Repository Owner
User
Repository Details
Programming Languages
Tags
Topics
Join Our Newsletter
Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.
Related MCPs
Discover similar Model Context Protocol servers
Azure MCP Server
Connect AI agents with Azure services through Model Context Protocol.
Azure MCP Server provides a seamless interface between AI agents and Azure services by implementing the Model Context Protocol (MCP) specification. It enables integration with tools like GitHub Copilot for Azure and supports a wide range of Azure resource management tasks directly via conversational AI interfaces. Designed for extensibility and compatibility, it offers enhanced contextual capabilities for agents working with Azure environments.
- ⭐ 1,178
- MCP
- Azure/azure-mcp
Kanboard MCP Server
MCP server for seamless AI integration with Kanboard project management.
Kanboard MCP Server is a Go-based server implementing the Model Context Protocol (MCP) for integrating AI assistants with the Kanboard project management system. It enables users to manage projects, tasks, users, and workflows in Kanboard directly via natural language commands through compatible AI tools. With built-in support for secure authentication and high performance, it facilitates streamlined project operations between Kanboard and AI-powered clients like Cursor or Claude Desktop. The server is configurable and designed for compatibility with MCP standards.
- ⭐ 15
- MCP
- bivex/kanboard-mcp
MyMCP Server (All-in-One Model Context Protocol)
Powerful and extensible Model Context Protocol server with developer and productivity integrations.
MyMCP Server is a robust Model Context Protocol (MCP) server implementation that integrates with services like GitLab, Jira, Confluence, YouTube, Google Workspace, and more. It provides AI-powered search, contextual tool execution, and workflow automation for development and productivity tasks. The system supports extensive configuration and enables selective activation of grouped toolsets for various environments. Installation and deployment are streamlined, with both automated and manual setup options available.
- ⭐ 93
- MCP
- nguyenvanduocit/all-in-one-model-context-protocol
Klavis
One MCP server for AI agents to handle thousands of tools.
Klavis provides an MCP (Model Context Protocol) server with over 100 prebuilt integrations for AI agents, enabling seamless connectivity with various tools and services. It offers both cloud-hosted and self-hosted deployment options and includes out-of-the-box OAuth support for secure authentication. Klavis is designed to act as an intelligent connector, streamlining workflow automation and enhancing agent capability through standardized context management.
- ⭐ 5,447
- MCP
- Klavis-AI/klavis
Unichat MCP Server
Universal MCP server providing context-aware AI chat and code tools across major model vendors.
Unichat MCP Server enables sending standardized requests to leading AI model vendors, including OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek, Alibaba, and Inception, utilizing the Model Context Protocol. It features unified endpoints for chat interactions and provides specialized tools for code review, documentation generation, code explanation, and programmatic code reworking. The server is designed for seamless integration with platforms like Claude Desktop and installation via Smithery. Vendor API keys are required for secure access to supported providers.
- ⭐ 37
- MCP
- amidabuddha/unichat-mcp-server
MCP Miro Server
Miro board integration for AI assistants via Model Context Protocol.
MCP Miro Server provides a standardized MCP server interface to the Miro platform, enabling AI assistants to access and manage Miro boards programmatically. It supports a wide range of board and item operations, including creating, listing, updating, and deleting boards and their contents. Secure OAuth token access ensures integration with users’ Miro accounts. Designed to work seamlessly with AI tools like Claude Desktop, it allows efficient and automated Miro workspace management.
- ⭐ 57
- MCP
- k-jarzyna/mcp-miro
Didn't find tool you were looking for?