Azure DevOps MCP Server
The Azure DevOps MCP Server enables AI models to interact with Azure DevOps, providing capabilities for managing work items, pull requests, pipelines, and more.
Overview
The Azure DevOps MCP Server brings Azure DevOps context to your agents, enabling AI models to interact with your Azure DevOps environment. It allows for managing work items, pull requests, test plans, builds, releases, and wiki pages directly from your code editor or AI assistant.
Official Server:
Developed and maintained by Microsoft
Key Features
Work Item Management
Create, update, query, and manage work items like bugs, tasks, and user stories.
Pull Request Operations
List, create, and update pull requests, and manage their comments and threads.
Pipeline & Build Interaction
Query pipeline status and trigger new pipeline runs.
Wiki Management
Create, update, and retrieve content from wiki pages.
Available Tools
Quick Reference
| Tool | Purpose | Category |
|---|---|---|
core_list_projects | List projects in your organization | Core |
wit_my_work_items | Retrieve work items for the authenticated user | Work Items |
wit_create_work_item | Create a new work item | Work Items |
repo_list_repos_by_project | List repositories for a given project | Repositories |
repo_create_pull_request | Create a new pull request | Repositories |
wiki_create_wiki_page | Create a new wiki page | Wiki |
Detailed Usage
core_list_projects▶
Retrieve a list of projects in your Azure DevOps organization.
use_mcp_tool({
server_name: "azure-devops",
tool_name: "core_list_projects",
arguments: {}
});
wit_create_work_item▶
Create a new work item in a specified project and work item type.
use_mcp_tool({
server_name: "azure-devops",
tool_name: "wit_create_work_item",
arguments: {
project: "MyProject",
type: "Bug",
title: "Fix authentication issue",
description: "Users are unable to log in."
}
});
repo_create_pull_request▶
Create a new pull request.
use_mcp_tool({
server_name: "azure-devops",
tool_name: "repo_create_pull_request",
arguments: {
repositoryId: "my-repo-id",
sourceRefName: "refs/heads/feature/new-feature",
targetRefName: "refs/heads/main",
title: "New Feature Implementation"
}
});
wiki_create_wiki_page▶
Create a new wiki page with specified content.
use_mcp_tool({
server_name: "azure-devops",
tool_name: "wiki_create_wiki_page",
arguments: {
project: "MyProject",
wikiIdentifier: "MyWiki",
path: "/NewPage",
content: "# My New Wiki Page\nThis is the content of my new wiki page."
}
});
Installation
{
"mcpServers": {
"azure-devops": {
"command": "npx",
"args": [
"-y",
"@microsoft/azure-devops-mcp"
],
"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"
}
}
}
}
Sources
Related Articles
Docker Integration MCP Servers
Docker MCP servers provide interfaces for LLMs to interact with Docker containers and services. These servers enable AI models to manage containers, handle image operations, and assist with Docker infrastructure tasks.
Pinecone MCP Server
Integrate Pinecone with your AI assistants using the Model Context Protocol (MCP) for enhanced vector database interactions.
Ethereum RPC MCP Server
A TypeScript MCP server that exposes the full Ethereum JSON-RPC surface, enabling AI assistants to query on-chain data, inspect contracts, and retrieve transaction details across EVM networks. Includes optional analytics and Zircuit-specific SLS methods.