"How to create and read issues in YouTrack project management" matching MCP servers:

Lets AI agents turn a repository's git history into proposed GitHub issues grouped into units of work, each with a commit checklist and links, then create and close them only after approval. Planning is read-only and creation defaults to a dry run, skipping anything that already exists.

A Model Context Protocol (MCP) server for YouTrack integration, providing a standardized interface for LLMs to interact with YouTrack's issue tracking, agile management, and knowledge base features.

A comprehensive Model Context Protocol server for YouTrack integration, providing extensive tools for issue tracking, project management, workflow automation, and team collaboration.

MCP server for comprehensive YouTrack integration, enabling issue management, work tracking, search, and knowledge base operations.

Enables AI assistants to interact with JetBrains YouTrack 2025.2 for managing issues, sprints, dependencies, time tracking, and knowledge base content. Supports CRUD operations, bulk commands, analytics with Gantt charts and critical path analysis, and covers ~80% of the YouTrack REST API.

Enables AI assistants to interact with JetBrains YouTrack for issue, project, and user management through natural language.

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

Enables LLMs to list, create, and comment on GitHub issues using your own GitHub identity via stdio transport.

Scaffold and audit Starter Series projects — MCP server, Claude Code skill, and CLI in one package.

Enables AI assistants to create projects, deploy files, container images, or Git repositories, attach domains, set write-only secrets, add Postgres, read logs, metrics, and failure summaries, and roll back.

A CLI tool that sets up a Model Control Protocol server and deploys it to Cloudflare Workers, allowing you to quickly create custom tools for your Cursor Agent just by writing TypeScript functions.

Enables project creation with validated flow and automatic registration via MCP, supporting scaffold, bootstrap, and validation tools.

Exposes GitHub issue operations as tools for LLM agents, enabling listing, creating, commenting on, closing, and searching issues via natural language.

An MCP server providing read-only access to Linear issues for language models, allowing them to fetch issue details and comments using a Linear API token.

Enables secure, read-only access to local project files (including text, DOCX, PDF, and XLSX) through MCP, with strict directory whitelisting and no write, edit, or command-execution tools.

Enables AI assistants to programmatically manage GitHub Project V2 boards with 100+ tools for issues, fields, workflows, and automation via MCP.

Enables AI assistants to manage project analysis, code metrics, documentation, Git operations, code quality, and file organization through natural language commands.

Enables AI assistants to discover, filter, and triage GitHub issues across repositories, with tools for fetching issue details, listing issues by state/labels, and finding related pull requests.

An enhanced dynamic MCP server management service that creates, runs, and manages Model Context Protocol servers with multi-language support and strict parameter validation.

MCP server that converts file contents into compact, line-numbered PNG images for vision models to read, reducing token usage by roughly 7x for large files.

Project Memory stores decisions, evidence, outcomes and reviewed lessons in local SQLite. Assistants retrieve bounded context through three MCP tools. People follow and plan work in a live workspace with an overview, sprint board, decision history, readable documents, skills and project maps. Offline exports remain available.

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.

A Model Context Protocol server that enables AI agents to access, search, and understand structured package documentation and source code from Git repositories. It automatically generates specialized tools to browse module overviews, components, and detailed documentation for technical libraries.

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.

A minimal MCP server using FastMCP to demonstrate tool creation, including a get_weather example.

MCP server for managing hierarchical project tracking with PostgreSQL. Enables AI agents to create, read, update, and delete projects, epics, stories, summaries, status updates, context, and issues.

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

Enables coding agents in different editors and MCP clients to share messages, project context, notes, task ownership, handoffs, and advisory file claims through a local SQLite-backed coordination server. Supports MCP stdio, MCP Streamable HTTP, a JSON HTTP API, and a local CLI for multi-project agent collaboration.

Enables AI agents to query a repository's verified semantic model, including capabilities, ownership, contracts, constraints, impact, health, and verification status, without re-deriving project facts. It exposes read-only tools for inspecting, reasoning about, and verifying the provenance-tracked surface.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.