"Non-Docker Implementation of Jira with MCP" matching MCP servers:

Enables AI assistants to interact with Atlassian Jira Cloud, allowing users to manage projects, issues, comments, and workflows through natural language commands.

Wraps the Docker Engine API as MCP tools for container and image management. Reduces token consumption by providing typed tools with default summaries and field selection.

Enables an AI agent to run and inspect containers, build and pull images, manage volumes and networks, drive Compose projects, clean up, and run self-checking practice labs. Startup modes restrict it to read-only, labs-only, or full Docker control with confirmation before dangerous operations.

Enables LLMs to search Docker Hub repositories, discover container images, and manage Docker Hub repositories and tags through natural language queries. Supports both public content access and authenticated operations with Docker Personal Access Tokens.

Enables inspecting, orchestrating, and troubleshooting Docker Engine and Docker Compose environments through six consolidated high-leverage MCP tools.

A tool that helps AI agents interact with Docker containers on local or remote machines, allowing users to manage and troubleshoot containers without Docker knowledge.

Enables issue search, creation, updates, comments, status transitions, and project listing in Jira, purpose-built for security incident management and SOC workflows.

Universal Docker MCP server for AI assistants (Cursor, Claude Desktop). Manage Docker containers, execute commands, query databases, and handle environment configurations — all through natural language.

Docker container, image, volume, network, and compose management from your AI assistant.

Enables AI assistants to manage Docker containers and Compose stacks through natural language, including lifecycle operations, logs, stats, and secure remote access.

An MCP server that enables AI assistants to manage Docker containers, images, networks, and volumes through a standardized interface. It supports comprehensive operations like container lifecycle management and image pulling while ensuring correct handling of command and environment variable arrays.

MCP server providing access to JIRA data with relationship tracking, optimized payloads, and data cleaning for AI contexts. Supports both Jira Cloud and Server/Data Center.

Enables AI assistants to access and manage Jira boards, sprints, epics, issues, JQL searches, transitions, comments, worklogs, projects, users, and any REST endpoint across Jira Cloud and Data Center.

Enables AI agents to manage Docker containers, images, Compose stacks, health checks, and logs through a unified MCP interface, ensuring containers stay running with self-healing capabilities.

Enables MCP clients to work with self-hosted Jira Server / Data Center 8.x through entity-based core tools, JSON-declared plugin tools, and bundled Zephyr Scale. It supports issue, comment, worklog, attachment, project, user, link, watcher, agile, and test management operations using Basic Auth or PAT with runtime field discovery.

Enables spawning ephemeral Linux sandbox containers using Docker and executing commands through an interactive TTY interface. Supports collaborative terminal sessions where both AI clients and humans can simultaneously interact with the same container.

Provides Docker management tools for AI agents, including inspecting containers, images, Dockerfiles, and Compose configurations.

Manages Docker containers, images, and Compose stacks on a remote host over SSH, with file sync and deploy orchestration.

Provides JIRA issue search, retrieval, and update functionalities via MCP.

Enables interacting with Jira for issue search, retrieval, project listing, and project details through natural language queries via the MCP protocol.