Open Issues Need Help
View All on GitHubAI Summary: Evaluate the feasibility of integrating the `mcp-evals` tool into the Azure MCP Server's end-to-end testing framework to automate the evaluation of agent responses based on five defined metrics. This involves researching the tool, assessing compatibility with the existing testing infrastructure, and potentially implementing the integration.
AI Summary: The task is to investigate the feasibility and process of packaging the Azure MCP Server (azmcp) as a DXt package for integration with Claude Desktop, leveraging the DXt specification from anthropics/dxt. This involves understanding both the Azure MCP Server's architecture and the DXt packaging requirements to determine compatibility and create a suitable package.
AI Summary: The task is to onboard Azure Kubernetes Service (AKS) as a new tool within the existing Azure MCP Server. This involves defining the commands for AKS interaction (cluster creation, management, diagnostics), handling authentication, and integrating it seamlessly with the existing framework. The work includes defining the agent scenarios and setting up the necessary configurations.
AI Summary: The task is to add support for Azure Spring Apps to the Azure MCP Server. This involves implementing the commands listed in the issue description (create, deploy, manage, debug, etc.) within the MCP framework, allowing AI agents to interact with Azure Spring Apps via the Model Context Protocol. This requires familiarity with the Azure Spring Apps service, the MCP specification, and the Azure MCP Server's existing codebase.
AI Summary: The task is to add support for Azure Container Apps to the Azure MCP Server. This involves implementing the commands exposed by the Container Apps VS Code extension within the MCP framework, allowing AI agents to interact with Container Apps through natural language prompts. This includes creating, configuring, deploying, and deleting Container Apps and their related resources.
AI Summary: The task is to add support for Azure App Service to the existing Azure MCP Server. This involves implementing the commands listed in the issue description, allowing AI agents to interact with Azure App Service resources through the MCP protocol. The implementation should follow the existing structure and design of the Azure MCP Server, ensuring seamless integration with the VS Code extension and other Azure services.
AI Summary: The task is to add support for Azure Functions to the Azure MCP Server. This involves implementing the various commands listed in the issue description (creation, configuration, deployment, management, logging, debugging, and access-related operations) within the existing MCP Server framework, ensuring seamless integration with the Azure Functions service and proper authentication.
AI Summary: The task is to add Azure Virtual Machines support to the Azure MCP Server. This involves implementing the commands for creating, configuring, managing, accessing, and updating virtual machines, as listed in the provided issue. The implementation should integrate seamlessly with the existing Azure MCP Server architecture and utilize the Azure SDKs for Virtual Machines.
AI Summary: The task is to add Azure Container Registry (ACR) support to the Azure MCP Server. This involves creating new MCP commands for ACR operations such as creating and deleting registries, managing repositories, building and tagging images, and accessing ACR resources through the Azure portal. The implementation should align with the existing MCP specification and integrate seamlessly with the Azure MCP Server's existing framework.
AI Summary: The task is to add Azure Virtual Network (VNet) functionality to the Azure MCP Server. This involves designing and implementing MCP commands and tools to allow AI agents to interact with and manage VNets, including provisioning, configuring IP addressing, segmentation, routing, network security, and hybrid connectivity. The work includes defining agent scenarios and determining the timeline for implementation.
AI Summary: The task is to modify the Azure MCP Server to consistently return a `results` array in its responses, even when the array is empty. Currently, empty results omit the `results` field entirely, leading to ambiguity. The change should ensure that a `results: []` is always present for consistency, improving clarity for clients consuming the MCP Server's responses.