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

An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

Provides software design guidance via MCP, including SOLID principles, design patterns, pattern scaffolding, and heuristic code-smell detection to help review and refactor code.

An MCP server that facilitates interactive software development planning by breaking down projects into manageable tasks, tracking progress, and saving implementation plans.

Enables converting software development requirements into traceable estimates, WBS breakdowns, PERT calculations, risk registers, roadmaps, quotations, and professional PDF proposals or action plans. It supports reviewing assumptions, exclusions, scope gaps, and commercial documentation before sending deliverables to clients.

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

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

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.

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.

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.

Intent-based project documentation server that automatically maps natural language queries to the right sources (plans, todos, roadmap, docs) and provides comprehensive task management with dependency tracking, backlog promotion, and archival workflows.

Exposes employee leave-management operations (add employees, check balance, apply/cancel leave, view history) as MCP tools for AI clients like Claude Desktop to call directly.

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.

A FastMCP server that exposes predefined artifacts as Resources and project lifecycle operations as Tools for creating, updating, deploying, debugging, testing, monitoring, and configuring projects with minimal token usage.

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.

Analyzes Python project structure by exploring directory trees, extracting outlines from Python and Markdown files, and inspecting OpenAPI specifications.

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.

Connects AI assistants to your n8n instance to manage workflows, executions, credentials, and user settings through 31 specialized tools. It enables users to perform n8n operations like workflow creation, activation, and execution history retrieval via natural language.

A local-first Model Context Protocol server that provides LLM agents with structured access to e-commerce data (products, inventory, orders, sales analytics) using a realistic mock dataset, zero configuration, and a swappable DataProvider interface for live APIs.

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.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida

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

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

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

Enables an AI assistant to administer a Jira Cloud site with 78 purpose-built tools for behind-the-scenes admin work like custom fields, permission schemes, workflows, screens, issue-type schemes, groups, project roles, saved filters, and bulk operations.

A Python framework that exposes developer tools through MCP, REST API, and CLI from a single shared registry, enabling AI assistants, HTTP clients, and terminal users to access the same tools.

A stateful MCP server that remembers what your AI agent has already seen.