ClickUp MCP Server Integration

What does “ClickUp” MCP Server do?

The ClickUp MCP Server integrates ClickUp project management with AI assistants via the Model Context Protocol (MCP). This server acts as a bridge, allowing AI models to access and interact with ClickUp data, such as tasks, projects, and lists, through standardized MCP endpoints. By connecting AI assistants with external data sources like ClickUp, it enhances development workflows by enabling seamless task tracking, project updates, and automation of repetitive project management actions. This integration empowers developers and teams to query project status, automate task creation, and manage workflows programmatically, all from within their preferred AI or LLM-powered environments.

List of Prompts

No information available.

List of Resources

No information available.

List of Tools

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Use Cases of this MCP Server

No information available.

How to set it up

Windsurf

1. Ensure Node.js is installed on your system.
2. Locate the windsurf.config.json configuration file.
3. Add the ClickUp MCP Server using the following JSON snippet:

   {
     "mcpServers": {
       "clickup-mcp": {
         "command": "npx",
         "args": ["@clickup/mcp-server@latest"]
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify the ClickUp MCP Server is running from the Windsurf dashboard.

Securing API Keys

Set your ClickUp API key as an environment variable and reference it in your configuration:

{
  "mcpServers": {
    "clickup-mcp": {
      "env": {
        "CLICKUP_API_KEY": "${CLICKUP_API_KEY}"
      },
      "inputs": {
        "api_key": "${CLICKUP_API_KEY}"
      }
    }
  }
}

Claude

1. Ensure Node.js is installed.
2. Locate or create the claude.config.json file.
3. Add the ClickUp MCP Server configuration:

   {
     "mcpServers": {
       "clickup-mcp": {
         "command": "npx",
         "args": ["@clickup/mcp-server@latest"]
       }
     }
   }
   

4. Save the file and restart Claude.
5. Confirm the MCP server appears in Claude’s integrations.

Cursor

1. Install Node.js.
2. Open the Cursor settings JSON file.
3. Add the ClickUp MCP Server:

   {
     "mcpServers": {
       "clickup-mcp": {
         "command": "npx",
         "args": ["@clickup/mcp-server@latest"]
       }
     }
   }
   

4. Save and restart Cursor.
5. Verify integration in the Cursor UI.

Cline

1. Install Node.js.
2. Edit or create cline.config.json.
3. Insert the following configuration:

   {
     "mcpServers": {
       "clickup-mcp": {
         "command": "npx",
         "args": ["@clickup/mcp-server@latest"]
       }
     }
   }
   

4. Save and restart Cline.
5. Confirm that ClickUp MCP Server is accessible from Cline’s MCP menu.

Note: Always secure API keys and sensitive credentials using environment variables as shown in the examples above.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "clickup-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “clickup-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the information available, the ClickUp MCP Server repository provides basic integration and setup instructions but lacks publicly documented resources, prompts, or tools. The presence of a license and moderate community engagement are positives, but the lack of detail lowers the utility for developers seeking advanced integrations.

Our opinion

MCP Score: 4/10
While ClickUp MCP Server provides a solid foundation for integrating ClickUp with MCP, the lack of documented tools, resources, and prompts significantly limits its immediate usability. Better documentation and examples would improve its score.

MCP Score