"Information about Azure OpenAI" matching MCP servers:

Enables natural language exploration of Azure environments by generating and executing KQL queries against Azure Resource Graph. Supports multi-tenant configurations, subscription scoping, and provides direct access to Azure resource information through conversational interactions.

Enables AI assistants to interact with an on-premise Azure DevOps Server 2022, allowing users to list, view, create, and update work items through natural language.

Enables AI assistants to manage work item attachments on Azure DevOps Server (on-premise) via the REST API, supporting listing, uploading, deleting, and downloading attachments.

Check whether an LLM model id is deprecated, retiring, or retired, and what to migrate to. Covers OpenAI, Anthropic, Azure, Bedrock, Google, and Cohere from each provider's own deprecation pages.

Enables AI assistants to search, compare, and get detailed information about MCP servers from the mcpcatalogs.com directory.

MCP server for Azure Service Bus that enables sending messages, inspecting queues and subscriptions, and purging test data. Complements the built-in Azure MCP server by adding write operations.

Live operational status for 2,400+ major software services — AWS, GitHub, Stripe, OpenAI, Cloudflare, and more — pulled from each provider's official status page and returned as a normalised up / degraded / down result for any service you ask about.

Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.

MCP-NixOS is a Model Context Protocol server that provides real-time, accurate information about NixOS packages, options, Home Manager, and nix-darwin configurations, preventing AI assistants from hallucinating about NixOS resources and enabling them to deliver factual system configuration guidance.

Provides access to Aceternity UI component library documentation, enabling AI assistants to browse, search, and retrieve detailed information about components.

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.

A Model Context Protocol server that allows AI assistants to search for and retrieve information about OpenTofu providers, modules, resources, and data sources from the OpenTofu Registry.

Enables AI assistants to interact with Azure DevOps Server 2022 through natural language, enabling queries and operations on pipelines, pull requests, builds, and repositories.

Enables AI assistants to search, create, update, and manage work items in Azure DevOps using natural language.

An MCP server providing comprehensive HubSpot CMS development documentation, enabling users to get contextual information about building HubSpot websites through natural language.

An MCP server that exposes 41 Azure DevOps tools to AI assistants, enabling management of pipelines, repositories, pull requests, releases, work items, test management, and wikis through natural language.

Enables AI assistants to search, analyze, and retrieve detailed information about Dart and Flutter packages from pub.dev. Supports package discovery, version management, dependency analysis, and documentation access.

A Model Context Protocol server that allows interaction with the RubyGems.org API to fetch metadata about Ruby packages, search gems, and explore dependencies and ownership information.

An MCP server for Azure DevOps that allows users to manage work items, sprints, iterations, and attachments. It supports custom WIQL queries and includes pre-defined prompts for common tasks like sprint planning, bug reporting, and daily standup generation.

An MCP server that enables reviewing Azure DevOps Pull Request comments using the Azure CLI, with features like comment retrieval and status filtering.