ClickUp MCP Server

The ClickUp MCP Server bridges the gap between AI assistants and the ClickUp productivity platform, allowing natural language agents to read, create, and update tasks directly within a user’s workspace. By exposing ClickUp’s RESTful API through the Model Context Protocol, developers can give Claude (or any MCP‑compatible client) a seamless way to manage projects without leaving the conversational interface. This eliminates context switching, reduces friction in task creation, and enables agents to surface relevant information from ClickUp as part of a larger workflow.

At its core, the server authenticates with ClickUp using a personal API token and runs in Stdio mode, meaning the MCP client spawns it as a child process and communicates via standard input/output. This lightweight architecture keeps the server portable across operating systems and simplifies deployment: a single command or Smithery installation is all that’s required. Once running, the server offers a rich set of tools for task, team, list, board, and space management—each tool corresponds to a specific ClickUp endpoint and accepts the same parameters that a developer would pass in an HTTP request.

Key capabilities include:

• Task creation and updates with fine‑grained control over status, priority, assignees, due dates, and tags.
• Retrieval of organizational structure such as teams (workspaces), spaces, folders, and lists, enabling the assistant to navigate hierarchy automatically.
• Board and space creation for dynamic project scaffolding, allowing agents to set up new collaborative areas on demand.

These features unlock practical use cases: an AI assistant can automatically pull tasks from a backlog, propose new subtasks based on project milestones, or generate status reports that aggregate data across multiple spaces. In agile environments, the server can help sprint planning by creating tasks from user stories and assigning them to appropriate team members. For project managers, the assistant can fetch all open tasks in a space and suggest prioritization based on due dates or custom tags.

Integration into AI workflows is straightforward. Once the server is registered in an MCP client, any prompt can invoke a tool by name—e.g., “Create a task named ‘Review PR #123’ in list 4567.” The client serializes the request, sends it to the server via Stdio, and streams back the result. Because MCP standardizes tool discovery and invocation, developers can mix ClickUp operations with other external services (e.g., GitHub, Slack) in a single conversational session, creating powerful end‑to‑end automation pipelines.

What sets this server apart is its developer‑friendly configuration: authentication is handled via a single environment variable, and optional logging or encryption keys can be added without modifying the codebase. The server’s modular design also means that new ClickUp endpoints can be exposed as additional tools with minimal effort. For teams already invested in ClickUp, this MCP server provides a low‑overhead bridge to AI assistants, turning conversational commands into actionable project updates and enabling smarter, context‑aware collaboration.