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securityA
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qualityA Model Context Protocol server providing AI assistants with comprehensive project, task, and subtask management capabilities with project-specific storage.
Last updated -
205
23
TypeScript
MIT License
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Why this server?
This server directly addresses task and subtask management, which aligns with the user's request for task assignment.
Why this server?
This server explicitly provides task management in a queue-based system, covering planning, execution, and completion phases which can relate to task assignment and re-shuffling.
Why this server?
Similar to the above, it focuses on managing tasks in a queue-based system, with planning, execution, and completion phases, suitable for task assignment and rearrangement.
Why this server?
Enables LLMs to interact with GitHub issues by providing details as tasks, allowing for seamless integration and task management through GitHub's platform.
Why this server?
A simple note-taking MCP server for recording and managing notes with AI models, which can be used to store and manage tasks.
Why this server?
Offers tools for working with CircleCI, which is often used in automated workflows involving task execution and dependency management.
Why this server?
Enables AI integrations with ClickUp tasks, supporting resource management, task operations, workspace organization, and AI-powered task recommendations through a standardized protocol.
Why this server?
Connects 'yt-dlp' with LLMs via the Model Context Protocol, allowing users to download YouTube content and integrate it with Dive and other MCP-compatible LLMs. While not directly task assignment, it can be used for educational purposes.
Why this server?
Provides capabilities for searching Jira issues using JQL and retrieving detailed issue information which supports managing existing and pre-listed tasks.
Why this server?
A lightweight server for AI assistants to manage tasks with notes in Obsidian vault. Allows organizing tasks and notes.