"Solutions for Automating Operations in Data Centers and Cloud Environments" matching MCP servers:

Enables AI assistants to run local-first operations checks, review evidence, and manage durable tickets in a SQLite-backed ledger through self-describing MCP tools.

MCP server for interacting with Jira Cloud instances. Enables issue management, JQL queries, project and sprint management, and batch operations via natural language interfaces.

Enables management of multiple Jira Cloud instances through MCP, including workspace linking, issue creation and editing, workflow transitions, attachment retrieval, and administration via a web interface.

Provides UK-centric date calculations including bank holiday integration, sprint planning tools, and specialized Asana workflow automation. It enables users to calculate working days, track upcoming holidays, and manage project schedules specifically within the Europe/London timezone.

An MCP server exposing internal business operations as tools — task management (create, list, update status) and RAG-style semantic search over an internal knowledge base (leave, expense, and onboarding policies) that any MCP-compatible AI agent can call directly for grounded, non-hallucinated answers.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables AI assistants to manage CRM deals and tasks on Aspro Cloud, including CRUD operations on deals, tasks, users, pipelines, and workflows.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

Enables AI clients to access a shared, authenticated memory and project management system with durable storage, task tracking, roadmaps, and semantic search, deployed on Cloudflare.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables AI assistants to interact with Zephyr Scale Cloud for test management, including test cases, cycles, plans, folders, priorities, and statuses via the MCP protocol.

An MCP server that connects AI assistants to Xray Cloud for Jira test management, enabling natural language interaction with tests, test plans, executions, and CI result imports.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Enables AI-powered project management by connecting Claude to Planka kanban boards via 75+ MCP tools for creating, updating, and managing projects, boards, lists, and cards.

Enables AI assistants to deeply introspect Jira Data Center configurations — including workflows, schemes, automation, and Assets — through 76 read-only tools, without any modification capability.

A Model Context Protocol (MCP) server that connects AI assistants to Jira Server/Data Center, enabling issue management, JQL search, sprint tracking, and natural language interaction with Jira.

MCP server for Xray Cloud test management that enables importing automation results and managing tests, test executions, and test sets in Jira.

Enables interaction with Azure DevOps through natural language in Cursor IDE. Supports work item management, pull requests, builds, releases, test management, and guided workflows for development teams, QA testers, and release management.

Enables voice-driven task management by letting users view, select, complete, and reschedule tasks through natural-language commands and a native confirmation card with date parsing and batch handling.