Azure DevOps▌
by microsoft
Boost your productivity by managing Azure DevOps projects, pipelines, and repos in VS Code. Streamline dev workflows wit
Supercharge your workflow by bringing Azure DevOps commands directly into VS Code. The Azure DevOps MCP Server lets you manage projects, builds, releases, repos, work items, test plans, and more from your editor with simple prompts. Focused, easy-to-use tools offer clear access to Azure DevOps data, making routine tasks faster while keeping complexity out of your way. Perfect for anyone who wants to streamline DevOps work inside their coding environment.
github stars
★ 1.4K
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers using Azure DevOps for version control
- / DevOps teams managing sprints and iterations
- / Code reviewers handling pull requests
- / Project managers tracking work items
capabilities
- / Create and update pull requests
- / Manage work item iterations
- / List projects and repositories
- / Assign pull request reviewers
- / Retrieve team information
- / Create project iterations
what it does
Brings Azure DevOps functionality directly into VS Code, letting you manage projects, pull requests, work items, and repositories from your editor. Streamlines DevOps workflows without switching between tools.
about
Azure DevOps is an official MCP server published by microsoft that provides AI assistants with tools and capabilities via the Model Context Protocol. Boost your productivity by managing Azure DevOps projects, pipelines, and repos in VS Code. Streamline dev workflows wit It is categorized under developer tools, productivity. This server exposes 77 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Azure DevOps in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Azure DevOps is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
⭐ Azure DevOps MCP Server
Easily install the Azure DevOps MCP Server for VS Code or VS Code Insiders:
This TypeScript project provides a local MCP server for Azure DevOps, enabling you to perform a wide range of Azure DevOps tasks directly from your code editor.
📄 Table of Contents
- 📺 Overview
- 🏆 Expectations
- ⚙️ Supported Tools
- 🔌 Installation & Getting Started
- 🌏 Using Domains
- 📝 Troubleshooting
- 🎩 Examples & Best Practices
- 🙋♀️ Frequently Asked Questions
- 📌 Contributing
📺 Overview
The Azure DevOps MCP Server brings Azure DevOps context to your agents. Try prompts like:
- "List my ADO projects"
- "List ADO Builds for 'Contoso'"
- "List ADO Repos for 'Contoso'"
- "List test plans for 'Contoso'"
- "List teams for project 'Contoso'"
- "List iterations for project 'Contoso'"
- "List my work items for project 'Contoso'"
- "List work items in current iteration for 'Contoso' project and 'Contoso Team'"
- "List all wikis in the 'Contoso' project"
- "Create a wiki page '/Architecture/Overview' with content about system design"
- "Update the wiki page '/Getting Started' with new onboarding instructions"
- "Get the content of the wiki page '/API/Authentication' from the Documentation wiki"
🏆 Expectations
The Azure DevOps MCP Server is built from tools that are concise, simple, focused, and easy to use—each designed for a specific scenario. We intentionally avoid complex tools that try to do too much. The goal is to provide a thin abstraction layer over the REST APIs, making data access straightforward and letting the language model handle complex reasoning.
⚙️ Supported Tools
See TOOLSET.md for a comprehensive list.
🔌 Installation & Getting Started
For the best experience, use Visual Studio Code and GitHub Copilot. See the getting started documentation to use our MCP Server with other tools such as Visual Studio 2022, Claude Code, and Cursor.
Prerequisites
- Install VS Code or VS Code Insiders
- Install Node.js 20+
- Open VS Code in an empty folder
Installation
✨ One-Click Install
After installation, select GitHub Copilot Agent Mode and refresh the tools list. Learn more about Agent Mode in the VS Code Documentation.
🧨 Install from Public Feed (Recommended)
This installation method is the easiest for all users of Visual Studio Code.
🎥 Watch this quick start video to get up and running in under two minutes!
Steps
In your project, add a .vscode\mcp.json file with the following content:
{
"inputs": [
{
"id": "ado_org",
"type": "promptString",
"description": "Azure DevOps organization name (e.g. 'contoso')"
}
],
"servers": {
"ado": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@azure-devops/mcp", "${input:ado_org}"]
}
}
}
🔥 To stay up to date with the latest features, you can use our nightly builds. Simply update your mcp.json configuration to use @azure-devops/mcp@next. Here is an updated example:
{
"inputs": [
{
"id": "ado_org",
"type": "promptString",
"description": "Azure DevOps organization name (e.g. 'contoso')"
}
],
"servers": {
"ado": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@azure-devops/mcp@next", "${input:ado_org}"]
}
}
}
Save the file, then click 'Start'.

In chat, switch to Agent Mode.
Click "Select Tools" and choose the available tools.

Open GitHub Copilot Chat and try a prompt like List ADO projects. The first time an ADO tool is executed browser will open prompting to login with your Microsoft account. Please ensure you are using credentials matching selected Azure DevOps organization.
💥 We strongly recommend creating a
.github\copilot-instructions.mdin your project. This will enhance your experience using the Azure DevOps MCP Server with GitHub Copilot Chat. To start, just include "This project uses Azure DevOps. Always check to see if the Azure DevOps MCP server has a tool relevant to the user's request" in your copilot instructions file.
See the getting started documentation to use our MCP Server with other tools such as Visual Studio 2022, Claude Code, and Cursor.
🌏 Using Domains
Azure DevOps exposes a large surface area. As a result, our Azure DevOps MCP Server includes many tools. To keep the toolset manageable, avoid confusing the model, and respect client limits on loaded tools, use Domains to load only the areas you need. Domains are named groups of related tools (for example: core, work, work-items, repositories, wiki). Add the -d argument and the domain names to the server args in your mcp.json to list the domains to enable.
For example, use "-d", "core", "work", "work-items" to load only Work Item related tools (see the example below).
{
"inputs": [
{
"id": "ado_org",
"type": "promptString",
"description": "Azure DevOps organization name (e.g. 'contoso')"
}
],
"servers": {
"ado_with_filtered_domains": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@azure-devops/mcp", "${input:ado_org}", "-d", "core", "work", "work-items"]
}
}
}
Domains that are available are: core, work, work-items, search, test-plans, repositories, wiki, pipelines, advanced-security
We recommend that you always enable core tools so that you can fetch project level information.
By default all domains are loaded
📝 Troubleshooting
See the Troubleshooting guide for help with common issues and logging.
🎩 Examples & Best Practices
Explore example prompts in our Examples documentation.
For best practices and tips to enhance your experience with the MCP Server, refer to the How-To guide.
🙋♀️ Frequently Asked Questions
For answers to common questions about the Azure DevOps MCP Server, see the Frequently Asked Questions.
📌 Contributing
We welcome contributions! During preview, please file issues for bugs, enhancements, or documentation improvements.
See our Contributions Guide for:
- 🛠️ Development setup
- ✨ Adding new tools
- 📝 Code style & testing
- 🔄 Pull request process
⚠️ Please read the Contributions Guide before creating a pull request.
🤝 Code of Conduct
This project follows the Microsoft Open Source Code of Conduct. For questions, see the FAQ or contact [email protected].
📈 Project Stats
FAQ
- What is the Azure DevOps MCP server?
- Azure DevOps is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Azure DevOps?
- This profile displays 35 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.4 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.4★★★★★35 reviews- ★★★★★Anika Zhang· Dec 12, 2024
Useful MCP listing: Azure DevOps is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Arya Park· Dec 8, 2024
Azure DevOps reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Chaitanya Patil· Dec 4, 2024
Azure DevOps reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Arya Wang· Nov 27, 2024
I recommend Azure DevOps for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Piyush G· Nov 23, 2024
I recommend Azure DevOps for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Amelia Tandon· Nov 3, 2024
Strong directory entry: Azure DevOps surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Daniel Brown· Oct 22, 2024
I recommend Azure DevOps for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Olivia Garcia· Oct 18, 2024
Strong directory entry: Azure DevOps surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Shikha Mishra· Oct 14, 2024
Strong directory entry: Azure DevOps surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Sophia Garcia· Sep 13, 2024
According to our notes, Azure DevOps benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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