"Information about Jira project management software" matching MCP servers:

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.

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.

Connects to Jira with Xray Test Management to extract test cases related to tickets and list test executions.

Security scanner for MCP servers and AI-generated code. Detects leaked API keys, PII, prompt injection, and MCP misconfigs with A-F security grades.

Enables Claude to read Jira CSV/JSON backlog exports, audit tickets for test readiness, and generate validated Gherkin acceptance scenarios tied to ticket criteria. It also tracks acceptance-criteria coverage and flags ambiguities or missing information for Product Owner follow-up.

Enables AI assistants to interact with a self-hosted Jira clone for testing, supporting project and issue management, comments, and search via MCP tools.

Enables to interact with Jira AIO Test Case Management System, allowing retrieval of test cases, projects, folders, and search functionality.

Enables comprehensive test management with JIRA's Zephyr system, allowing users to create and manage test plans, execute test cycles, track progress, and generate reports through natural language.

Enables access to Xray Cloud test management on Jira Cloud through its REST v2 and GraphQL APIs, with configurable read/write toolsets, single-tool selection, and read-only or per-request credential modes.

MCP server to interact with the QMetry for Jira API, enabling management of test cases, test cycles, test plans, and more through well-defined tools.

Provides JIRA issue management and automation through MCP tools and standalone scripts, enabling reading, searching, analyzing, and modifying issues with batch processing and OCR capabilities.

Enables intelligent analysis of regression test failures and automatic discovery of solutions in JIRA. Analyzes test logs using AI-driven algorithms and matches errors with relevant JIRA issues through natural language interactions.

Enables reproducible evaluation of AI coding agents by exposing repository inspection, code editing, test running, and deterministic verification through MCP tools.

An intelligent MCP server for QA automation that enables AI agents to perform stateful API testing by converting Postman collections into MCP tools, with automatic authentication, session-based state management, and transparent error handling.

Enables AI assistants to interact with iOS Simulators and Android Emulators, allowing autonomous app development, UI interaction, profiling, and debugging through natural language.

A Model Context Protocol server that enables building Android projects and running tests directly in Visual Studio Code through extensions like Cline or Roo Code.

Enables building, running unit tests, and instrumented tests for Android projects through the MCP protocol.

A simple MCP server/client implementation for testing Hermes Agent, exposing basic tools like echo, add, and get_server_info via stdio.

Gives your AI the super power of traveling back in time to find what went wrong and fix the bug timeline.

Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.

Exposes nine tools over stdio to bridge Godot 4 and Unity 6 projects, enabling character-data loading, headless verification, combat simulation, and live telemetry workflows.

Lets any MCP client, such as Claude, browse attack suites and probes, run a full assurance assessment with all reports written out, send custom prompts or multi-turn histories and get leak, PII and refusal checks back for adaptive attacks, and read findings from an earlier assessment. This enables agent-driven red-teaming of a chatbot, RAG app or AI agent without leaving the chat client.

An MCP server that diagnoses Flutter + Stripe (flutter_stripe) setup issues — so Claude can check your project automatically.

Enables recurring website maintenance checks — domain registration, SSL certificates, uptime, technical SEO and accessibility — across a portfolio of client sites, using publicly available information. Results are returned as structured data and can be sorted by urgency into a client-ready report.

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.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

Visual CVE audit dashboard for npm, Python, Go, and Rust projects. Scans your project manifests (package-lock.json, requirements.txt, go.sum, Cargo.lock) against OSV.dev live data, opens a browser dashboard for human review, then applies fixes only after explicit confirmation. Supports multi-service monorepos in one command.

Scan any project or website for privacy compliance issues directly in your AI coding tool. Detects tracking tech, cookies, and third-party data collection. Works in Claude Code, Cursor, and Windsurf.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.