"Today we are excited to take our local MCP Server for Azure DevOps out of preview 🥳. Since the initial preview announcement, we've worked closely with early adopters and the community to incorporate feature suggestions and feedback. We've improved login and authorization, added and refined tooling, and introduced domains so users can scope active tools to stay under client limits. 🤷‍♂️ What is an MCP Server? A local MCP Server (Model Context Provider) is a tool that sits between your AI assistant (like GitHub Copilot) and your Azure DevOps organization."
"Its job is to inject rich, real-time context such as work items, pull requests, test plans, and more into the prompts sent to the LLM, allowing the assistant to provide more accurate and relevant answers tailored to your specific Azure DevOps project. The Azure DevOps MCP Server supports most of the main areas of the product, including work items, wiki, repos, search, and test plans."
"For an open-source project like this, the difference between public preview and general availability is small. You can expect the same level of engagement from us as we continue to monitor issues, incorporate community feedback and contributions, refine existing tools, and introduce new ones. The main change is that now that the project is generally available, we will be more deliberate about how we make updates to minimize the risk of breaking existing tools and ensure greater stability for everyone."
A local MCP Server for Azure DevOps is now generally available and runs inside customer networks or local development environments. The MCP Server injects rich, real-time context—work items, pull requests, test plans, wiki content, repos, and search—into prompts sent to LLM-based assistants to improve accuracy and relevance for specific projects. Improvements include enhanced login and authorization, refined tooling, and domains to scope active tools and control client limits. General availability brings a commitment to stability with more deliberate updates, continued community engagement, and ongoing incorporation of feedback and contributions. Setup requires following repository installation and configuration instructions.
Read at Azure DevOps Blog
Unable to calculate read time
Collection
[
|
...
]