"Using Jira MCP to comment on subtasks, read descriptions, and create a test plan" matching MCP servers:

Scaffold and audit Starter Series projects — MCP server, Claude Code skill, and CLI in one package.

Enables AI assistants to create projects, deploy files, container images, or Git repositories, attach domains, set write-only secrets, add Postgres, read logs, metrics, and failure summaries, and roll back.

A secure MCP server providing read-only access to Argo CD instances using browser session cookies, enabling querying of applications, projects, clusters, and repositories.

Enables test execution and management through MCP clients, allowing retrieval of projects, listing tests, executing tests with browser selection, and monitoring results.

It enables AI agents and CI to run profile-driven SOAP/REST service tests with automatic login/session handling, test-customer locking, masked transaction-log/HAR catalog import, and cross-environment scenario execution.

Facilitates unified execution and result parsing for various testing frameworks, including Bats, Pytest, Flutter, Jest, and Go, through a Model Context Protocol interface.

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.

Provides tools to execute Terraform commands, analyze plan outputs for resource changes, and generate detailed markdown reports. It supports custom environment variables and filtering patterns to streamline infrastructure analysis and management.

An end-to-end test MCP server built with FastMCP that exposes a REST API as a set of tools for AI agents. It enables LLMs to perform CRUD operations on an upstream API by mapping HTTP methods to MCP tools.

A minimal MCP server with greet, add, and whoami tools, designed to validate deployment pipelines and environment variable injection.

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

A test harness for MCP servers that validates server JSON, tool schemas, performs golden file diffing and schema drift detection, and generates signed test reports with Shields.io badges.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

A Model Context Protocol (MCP) server that provides Xcode-related tools for integration with AI assistants and other MCP clients.

Enables automatic generation of test scenarios from user stories uploaded to Claude desktop. Leverages MCP integration to streamline the test case creation process for development workflows.

Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.

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.

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.

MCP server for Azure DevOps Server 2022 (on-premises) that enables AI assistants to interact with work items, repositories, builds, and sprints through 29 tools.

MCP server wrapping the full VitoDeploy REST API to manage projects, servers, sites, databases, services, workers, SSL, DNS, and more through any MCP-compatible agent, with 108 tools covering every endpoint.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

An MCP server that integrates Cursor IDE with Xray Test Management for Jira, enabling management of tests, test executions, test plans, and import/export operations.

Integrates Qlane test management into AI coding editors, enabling agents to view projects, test targets, and test case counts, and plan tests for local diffs.

Enables MCP-capable agents to queue and evaluate real ComfyUI workflows through a live instance, returning structured pass/fail results without needing to know Playwright or ComfyUI internals.

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An MCP server that enables Claude to create and manage TestRail test cases directly from Jira or Azure DevOps user stories. It provides tools for section management and automated test case creation with built-in format enforcement and traceability links.

Enables comprehensive test management through SmartBear Zephyr Scale's REST API, supporting automated workflows for test cases, cycles, executions, folders, and linking tests to Jira issues through natural language.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

Enables coding agents to read Squally CI data, including test results, flakiness, and failure diagnostics.