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"task management" matching MCP servers:

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    A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.
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    MIT
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    A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.
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    Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.
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    MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.
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    Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.
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    A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.
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    AGPL 3.0
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    Enables AI assistants to manage WordPress networks through a MainWP Dashboard, including site management, updates, plugin/theme control, and bulk operations via natural language.
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    GPL 3.0
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    An MCP server for interacting with Reddit, enabling browsing, searching, content creation, and management with built-in safe mode and bot disclosure features.
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    Connects LLMs to your macOS Shortcuts library, enabling interactive workflows, discovery, and management through AppleScript and CLI integration.
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    A communication framework that enables multiple AI agents to collaborate through asynchronous messaging, agent registration, and discovery. It facilitates complex task coordination and real-time discussion across distributed agent workflows using the Model Context Protocol.
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