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

A Model Context Protocol server that provides tools for interacting with Docker images, containers, and registries, enabling AI assistants to search, analyze, and manage Docker resources through a standardized interface.

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

A comprehensive MCP server that provides advanced Docker operations through a unified interface with 16 MCP tools and 25+ CLI aliases, enabling secure container lifecycle management, multi-container orchestration, registry publishing, and system maintenance.

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Provides comprehensive access to Jira Cloud and Data Center instances for managing issues, epics, and attachments with AI-optimized data cleaning. It supports relationship tracking and dual transport modes via STDIO and Streamable HTTP.

Enables automated analysis of test suite traces to identify timing races and state pollution, helping detect flaky test non-determinism in CI/CD workflows such as Datadog CI or Trunk.

MCP server providing tools to verify task completion (tests pass and changes match claim) and confirm bug reproduction before fixing.

Enables interaction with Azure DevOps services through Personal Access Token authentication. Provides 75 tools for managing work items, builds, repositories, pull requests, and other DevOps operations via both CLI and HTTP API interfaces.

Integrates Jira and GitLab to enable AI agents to seamlessly manage issues, create branches, and automate SRE workflows from issue detection to fix deployment. Features AI-powered analysis for intelligent code generation and comprehensive automation across both platforms.

Enables AI agents and external systems to programmatically trigger and monitor Jenkins jobs, retrieve build status and logs via MCP standards.

Mneme exposes a governed Decision Index so MCP clients can propose candidate architectural decisions and query decision state, applicability, and traceability. Proposals remain non-authoritative: accepting or activating protections stays under explicit human control.

Automates the full setup and deployment of Ballerina + Apache ActiveMQ integrations inside a WSO2 Integrator workspace, from broker validation to a runnable BI-low-code-ready project.

Enables AI agents to retrieve the latest semantic version tags for container images from Docker Hub, GHCR, Quay, and other OCI registries, allowing them to pin specific versions for reproducible deployments.

Turns Claude Code into an interactive OpenWiFi triage assistant, providing tools for searching Linux wireless patches, Jira tickets, running LLM-based triage, backporting, and building OpenWiFi.

Enables AI coding agents to retrieve the latest stable versions of packages and tools across multiple ecosystems, preventing outdated dependency versions in generated code.

A reference MCP server for observing Vercel projects and deployments over stdio. It provides read-only tools to list and fetch details of Vercel projects and deployments.

An MCP server that scaffolds full-stack projects with consistent structure, Docker setup, CI/CD pipelines, and database configuration.

A Model Context Protocol server that lets development agents work with Odoo.sh from their development environment, listing branches, watching builds, and streaming logs. It sits on top of the odouche Python library's public interface.

Autonomous coding pipeline exposed as an MCP server: plan, dispatch, review, and merge software stories through worktree-isolated agents. A frontier model (Claude) handles judgment — planning, review, risk adjudication — while a local model does the implementation, gated by TDD and a merge-time test rerun on the rebased branch.

Enables LLMs to migrate Docker Compose applications to Kubernetes, including inspection, planning, manifest generation, validation, deployment with approval, verification, and diagnosis.