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URL: https://glama.ai/mcp/servers/integrations/clickup

⇱ ClickUp | Glama

  • Why this server?

    Enables AI agents to interact with ClickUp tasks, spaces, lists, and folders through a standardized protocol. Provides comprehensive task management (create, update, delete, move tasks), workspace organization tools, and supports natural language due dates with relative time expressions.

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    A Model Context Protocol server that enables AI agents to interact with ClickUp workspaces, allowing task creation, management, and workspace organization through natural language commands.
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  • Why this server?

    Provides tools for managing ClickUp tasks and lists, including retrieving, creating, and updating tasks, with support for task details, assignees, due dates, and statuses.

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    Enables integration with ClickUp's task management platform, allowing users to retrieve, create, update, and manage tasks and lists through the Model Context Protocol.
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  • Why this server?

    Provides comprehensive tools for managing ClickUp workspaces, including tasks, lists, folders, spaces, docs, chat, goals, sprints, time tracking, custom fields, webhooks, guests, and more via the ClickUp v2 and v3 APIs.

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    ClickUp MCP Pro exposes nearly every ClickUp operation as a typed Model Context Protocol tool — so Claude Code (and any MCP client) can drive your entire workspace: tasks, lists, folders, spaces, docs, chat, goals, sprints, time tracking, custom fields, webhooks, guests and more. When a niche endpoint isn't wrapped, clickup_raw reaches the rest of the API directly, giving you 100% coverage.
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  • Why this server?

    Allows AI agents to manage ClickUp tasks, spaces, folders, and lists, including creating, updating, moving, duplicating tasks, and retrieving workspace hierarchy.

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    Enables AI agents to manage ClickUp tasks, spaces, lists, and folders through natural language, supporting CRUD operations and workspace navigation.
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  • Why this server?

    Provides comprehensive access to the ClickUp API, enabling management of workspaces, spaces, folders, lists, tasks, comments, time tracking, goals, and views. It supports advanced features like custom fields, document collaboration, and chat interactions with token-efficient output optimized for AI agents.

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    A token optimised ClickUp CLI with built in MCP server that provides an efficient way to get data from ClickUp without consuming large amounts of LLM context
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    Apache 2.0

  • Why this server?

    Provides tools for accessing and manipulating ClickUp data including workspaces, spaces, folders, lists, tasks, docs, comments, and checklists, with capabilities for retrieving, creating, and updating various ClickUp resources.

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    ClickUp MCP Server enables AI assistants to seamlessly interact with your ClickUp workspace. This powerful integration allows Claude to create and manage tasks, access documents, organize folders and lists, add comments, and handle checklists—all through natural conversation.
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  • Why this server?

    Provides tools for managing ClickUp tasks and user profiles, including creating, updating, deleting, and listing tasks, as well as retrieving user information.

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    Enables natural language management of ClickUp workspaces, including task CRUD operations, task listing, and user profile retrieval via Claude Desktop.
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  • Why this server?

    Enables interaction with ClickUp's task management API, providing tools for creating, reading, updating, and deleting tasks, managing task organization, searching and filtering tasks, handling assignees and statuses, performing bulk operations, tracking time, and generating team analytics.

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    Enables AI assistants to interact with ClickUp's task management API for core project workflows, supporting operations like task creation, updates, search, assignment, and team analytics through natural language.
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  • Why this server?

    Provides tools for managing tasks, comments, tags, checklists, dependencies, custom fields, and workspace navigation in ClickUp.

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    Lightweight ClickUp MCP server for task management with 37 tools and token-optimized responses to reduce API verbosity.
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