"A server for creating JIRA tickets" matching MCP servers:

Enables semantic search and analysis of customer support tickets. Provides tools to search tickets, analyze the dataset, and retrieve individual tickets using natural language.

A read-only MCP server exposing TOTVS support tickets (Portal do Cliente) as tools for LLMs in Claude Code, Claude Desktop, and Cursor.

An async MCP server for JIRA integration, enabling AI assistants to search, create, and manage JIRA issues via JQL and other operations.

MCP server for Jira Cloud enabling issue tracking, comments, transitions, and attachments management through natural language.

MCP server for Jira Server/Data Center that enables issue retrieval, JQL search, comment posting, and Tempo worklog queries via the atlassian-python-api.

This MCP server provides unified read/write access to Jira Cloud tickets and Confluence Cloud pages, enabling search, retrieval, and updates. It automatically downloads log attachments from tickets into a shared directory for the companion Log Intelligence MCP to ingest.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Enables MCP clients to read and create Jira issues against Jira Cloud or Data Center through a self-hosted FastMCP server with secure authentication and configurable fields.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

MCP server for fetching Jira issue data via the Jira API.

This MCP server enables interaction with Atlassian products (Jira and Confluence), with additional tools for uploading attachments, embedding images, and commenting with images. It supports both Cloud and Server/Data Center deployments.

Enables coding agents to read Jira Cloud issues, search via JQL, and retrieve comments, attachments, and change history through a lightweight, context-efficient MCP toolset.

Exposes Jira task management (list, create with two-step confirmation, start) to AI agents while keeping credentials hidden, and deliberately does not handle git operations.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

Enables coding agents to turn Jira Cloud tickets into ready-to-build briefs, verify local branches against acceptance criteria, and prepare QA handoffs, with optional previewed and audited write-back.

Minimal MCP server for Jira with configurable tools to reduce token usage, starting from ~150 tokens for basic issue retrieval.

Provides AI models with full access to Jira Cloud functionality, enabling issue management, project tracking, sprint planning, and agile board operations through the Jira REST API v3 and Agile API 1.0.

Enables AI assistants to interact with self-hosted Jira instances for issue management, search, comments, and workflow transitions.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Enables querying and managing Jira issues and Confluence pages through their Cloud REST APIs, preserving markdown formatting via direct ADF conversion.

Provides AI assistants with tools to query, filter, and analyze JIRA issues stored in Snowflake, enabling natural language interaction with issue data.

Enables AI agents to interact with Jira and GitHub through MCP tools, including searching, creating, commenting on, and transitioning Jira issues and listing pull requests, summarizing diffs, creating issues, and commenting on GitHub.

Enables AI agents to manage Jira projects and issues using natural language, including creating, updating, searching issues, managing sprints, and more via the Jira API.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Unofficial Powershell MCP server

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

Connects AI assistants to Jira Service Management instances, providing 40 tools for managing service desks, requests, comments, customers, organizations, queues, SLA, approvals, and attachments.

MCP server that bridges Ableton Live with AI models, enabling real-time project inspection and control such as track overview, device parameters, and audio analysis.