"Servers for Searching Recently Updated Jira Issues" matching MCP servers:

Enables triage of GitHub issues by fetching and filtering issues, checking claim status, and listing new open issues across a watch-list.

A read-only Model Context Protocol server for Hyperliquid that exposes over 30 tools to query public market data and user state via the Hyperliquid Info API, without requiring a private key.

Lets agents read a GitHub repository's live issues through read-only tools for listing, filtering, fetching details with comments and cross-references, searching, and exploring labels and milestones, with transparent pagination and provenance notes.

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

Provides read-only access to Jira, enabling users to retrieve issue details, comment threads, linked-issue context, epic children, and JQL search results as compact Markdown.

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.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

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 workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.

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.

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

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.

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.

A Model Context Protocol server for Atlassian Jira and Confluence that bypasses corporate proxies and self-signed certificates, enabling read/write operations on issues, projects, pages, and spaces using Personal Access Tokens.

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