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

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

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 coding agents to deterministically audit test files for fake or fragile tests (no assertions, tautological or swallowed assertions, focused/skipped tests, fixed sleeps, real network calls) and to run the project's actual test runner, treating an exit-0 run with zero tests as a failure and flagging changed source files that lack test coverage.

MCP server that performs mutation testing and diff scoping to score how trustworthy tests are for detecting regressions in changed code.

A Model Context Protocol server for integrating JIRA with Claude, enabling AI assistants to create, search, update, and link JIRA tickets, as well as manage Zephyr test steps through natural language.

MCP server for Jira Cloud tailored for ALM projects with Zephyr Scale integration, enabling issue management, sprint tracking, and test step operations.

A minimal MCP server that tests Authgear's Dynamic Client Registration and resource-indicator flow, verifying JWTs bound to a specific resource.

A TypeScript-based test implementation for the Model Context Protocol (MCP) with example configurations and Jest test cases. Provides a development foundation for building and testing MCP server functionality.

A demo MCP server for testing and debugging tools, providing tools to get launches and trending words.

Lets AI agents ask which tests a Playwright or Vitest project contains, which are skipped and why, by reading the test source files statically. Nothing is executed, written, or sent over the network, and answers come back as paged JSON with summaries, filters, and scan diagnostics.

An automated testing MCP server that converts test cases into a fixed JSON format, runs them case-by-case, and provides a visual report with review support for cases that cannot be automatically judged.

Generates quality control plans and inspection reports from technical-drawing PDFs: tolerances, fits, threads, GD&T and surface finishes are extracted automatically by Imnoo's drawing analysis, numbered as balloons with acceptance limits and measuring instruments, and exported as a ballooned drawing PDF, an inspection package and an Excel measurement report.

An MCP server that gives AI coding agents the ability to analyze a Python repository's test health: coverage, flaky tests, and ML-based pull-request risk prediction.

Enables AI coding agents to run Foundry tests and builds and receive compact, structured failure reports with decoded reasons, fuzz counterexamples or invariant call sequences, logs, and short traces. It also distinguishes genuine test failures from cases where tests did not run, returning actionable errors instead of false zero-failure results.

Enables management of TestMu AI test projects, test cases, test runs, and integration with Jira, HyperExecute, and AI insights through natural language.

Test coverage intelligence MCP server for TypeScript and JavaScript projects. Analyzes coverage reports to find untested functions, computes cyclomatic complexity, and suggests test cases locally.

Gives AI assistants structured access to a test automation stack so they can run suites, inspect failure details and captured output, look up test data, and file Jira bugs (or drafts) only for confirmed defects. It works with any framework that emits JUnit XML, letting assistants triage flaky, environment, and test-data issues alongside real product defects.

Auto-generates and manages test cases for any project from feature descriptions, with tools for adding, listing, updating, and exporting test cases via Claude.

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

A specialized testing harness that enables AI assistants to thoroughly test other MCP servers by connecting to them, discovering their tools/resources/prompts, executing test calls, and performing end-to-end validation with LLM integration.