概览
What is Clickup Mcp?
A Model Context Protocol (MCP) server that enables AI assistants like Claude, Windsurf, and Cursor to interact with your ClickUp tasks. It provides rich task details, full comment history, inline image support, task search, and todo management.
How to use Clickup Mcp?
Configure the MCP server in your AI assistant’s settings by adding the ClickUp MCP entry with the npx command and your CLICKUP_API_KEY and CLICKUP_TEAM_ID environment variables. Once connected, ask your assistant to “Show me details for task CU-123456” or “Find tasks related to login functionality.”
Key features of Clickup Mcp
- Retrieve complete task information including status, creation date, and assignees
- Access full comment history for context
- View inline images in task descriptions and comments
- Search tasks using keywords
- List open todos (limited to 50 tasks)
- Adjustable image limit via
MAX_IMAGESenvironment variable (default 4)
Use cases of Clickup Mcp
- View detailed task data and comments for a specific ClickUp task
- Search for tasks related to a topic across your workspace
- Check your personal todo list of open tasks
- Get full context (comments + images) for individual tickets
FAQ from Clickup Mcp
What credentials are required?
You need a ClickUp API Key (starts with pk_) and your ClickUp Team ID (the ~7-digit number in the URL when in settings). Set them as CLICKUP_API_KEY and CLICKUP_TEAM_ID environment variables.
How can I change the number of images returned per task?
Set the MAX_IMAGES environment variable to your desired number. If not set, it defaults to 4. Note that most AI tools have constraints limiting the usable number of images.
What is the limit for the todo management feature?
The todo list is limited to 50 tasks to avoid flooding the AI assistant’s context.
Does this MCP support ClickUp Lists or Spaces?
No. Browsing Lists or Spaces is not currently supported due to performance issues with large instances.
What is language-aware search guidance?
If you set CLICKUP_PRIMARY_LANGUAGE (e.g., “de” for German) or the LANG environment variable, the searchTask tool’s description will recommend providing search terms in both English and that language for better results in multilingual workspaces.
