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ClickUp
Ask Claude, ChatGPT or any other MCP client about your ClickUp data in natural language chat. Query project completion rates across different workspaces, compare task counts between spaces, or analyze folder-level permissions and statuses without writing SQL or exporting CSV files. The AI reads your replicated ClickUp data and returns instant answers about team productivity, project bottlenecks, and workload distribution directly in your conversation.
Kondado replicates ClickUp data through an MCP server, making 3 pipelines available for analysis in Claude, ChatGPT, and other MCP clients. This setup exposes workspace configurations, space assignments, and folder structures across 125 fields, enabling detailed project management analytics through conversational AI. The same replicated data also powers ready dashboard templates in Power BI and Looker Studio for visual monitoring.
Marketing project managers can ask about campaign task completion trends across different spaces, while operations leads query workspace-level permission levels to audit team access controls. E-commerce coordinators analyze folder task counts to track inventory or product launch pipelines, and finance teams review project status distributions to forecast resource allocation and billing cycles. Each role gets specific operational insights by simply chatting with their AI assistant about current ClickUp metrics, eliminating the need for manual report building.
The ClickUp pipelines available through Kondado include detailed Workspaces, Spaces, and Folders endpoints that unlock specific project management insights when queried in natural language. Query the Workspaces pipeline to analyze task count distributions and permission levels across your organizational structure, or explore the Spaces pipeline to review multiple assignee configurations and custom status workflows across projects. The Folders pipeline reveals detailed task aggregation metrics and granular permission settings that help track project health and access controls at the container level. Cross-analyzing these three pipelines allows you to correlate workspace-level color coding and settings with specific folder task loads, or compare space assignee patterns against folder completion rates for comprehensive resource allocation planning. With automated updates running on a configurable schedule, your AI assistant always references current project states when answering questions about team productivity and project bottlenecks.
MCP is an open standard. Add the Kondado server to the connections of Claude (Web or Desktop), ChatGPT, or any other MCP client you use, and authorize via OAuth at app.kondado.com.br. Setup through the UI, no code.
Each item below is something Claude, ChatGPT or another MCP client already knows how to query — no schema setup, no manual mapping.
In 3 steps: connect on Kondado, pick dashboard or chat, analyze.
Connect ClickUp on Kondado at app.kondado.com.br and select a Via Kondado destination so your data lands ready for AI analysis and for the dashboard templates.
In Claude (Web or Desktop) or in ChatGPT, add the Kondado MCP server in the connection settings and authorize once via OAuth, the same GUI setup in both clients with no CLI or code needed.
Ask in chat using natural language about your ClickUp workspaces, spaces, and folders; for visual recurring monitoring, open a ready Power BI or Looker Studio dashboard template.
Same Kondado data, in chat through Claude, ChatGPT and other MCP clients.
How ready dashboards and chat via Claude / ChatGPT work together with your data via Kondado.
Try out all the features for free for 14 days