"Information about Jira" matching MCP servers:

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.

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

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.

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

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.

MCP server for managing test cases, cycles, and results in Zephyr Scale on self-hosted Jira. Enables AI agents to create, search, update, and delete test artifacts through natural language.

A read-only MCP server that exposes Zephyr Scale Cloud test data to review a Jira story's test coverage, answering whether tests are adequate and passing.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

Automated Playwright E2E test repair powered by a self-improving, governed MCP server that runs failing tests, collects failure artifacts, reasons about root causes, validates and applies fixes, and re-runs to verify.

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

Enables AI assistants to access RenderDoc capture data and assist with graphics debugging by retrieving draw calls, shader information, buffers, textures, and pipeline state.

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.

Allows LLM agents to query Playwright JSON test results for run summaries and failure information.

An MCP server that exposes the QMetry Test Management for Jira Cloud REST API as tools for MCP-compatible clients. It enables users to manage test cases, test cycles, test executions, test plans, folders, and automation rules through natural language interactions.

An MCP server that enables AI agents to drive Zephyr for Jira (Server/Data Center) test management via ZAPI. It exposes operations for test cycles, folders, executions, test steps, step results, and ZQL search over stdio for use with any MCP client.

Local MCP server for querying VCD waveform files via SQLite; enables AI agents to ask precise questions about signal values, transitions, and clock cycles without dumping raw VCD text.