Feature Requests

Currently the only way to disable AI is through ClickApps via Admin. This disables it for the entire team. I just want to remove this garbage from my own personal profile without impacting anyone else's workflow.

The video recordings generated by AI Notetaker are consistently blurry/low resolution, even after waiting for transcoding to complete. When reviewing meeting recordings to revisit screen shares, presentations, or demos, the quality makes it difficult to read on-screen text or see details clearly. It would be great to have an option for higher definition video recordings (720p or 1080p) so the playback is actually useful for reviewing visual content shared during calls.

I have a big problem because some of my team members use AI points, and I don't know how to control it. I'm paying for ClickUp AI and Notetaker, and I want to control who uses the points/credits because somebody from my team uses it too much, but I, as the owner of the company, want to use it!!!! I want to have control over that! Also, I want to buy points only for me as the owner of the company and space, and use them for myself. My studio team doesn't need it, so why do I need to pay for each member? I understand that more people means more data to analyze, but still why charge for all people when I just need more credits? Let's make it clearer and more flexible. Please, I need more tools to control AI use. Maybe you have them already. I'd appreciate any help with that. Have a nice day Maciej S.

It seems like a flaw that ClickUp Brain can edit the assignees of a task but can't remove followers when prompted specifically. Can this be expanded to include this?

Like you can do in ChatGPT or Claude.

Problem: The current AI Usage dashboard provides a high-level overview but lacks the necessary granularity for effective resource management. Currently, while Super Agents have a clear breakdown, other high-consumption features like Autopilot Agents, AI Cards, AI Fields, and AI Tasks only show aggregate costs. Furthermore, the dashboard prioritizes monetary value (USD) over the actual credit count, and lacks historical month-over-month reporting for trial/bonus pools. Proposed Solution: I suggest a comprehensive update to the AI Usage interface to include: Dual Metric Visibility: Display "Credits Consumed" alongside "Monetary Cost (USD)" as standard columns. Relying on tooltips (hovering) makes it difficult to compare usage across different workflows quickly. Granular Breakdown for All AI Features: Extend the "Super Agent" level of detail to Autopilot Agents, AI Fields, and AI Cards. We need to see: Which specific Agent/Automation triggered the usage. The location (List/Folder/Space) of the trigger. The User/Member responsible for the action. Historical Data & Period Filtering: Ability to filter usage by previous months or custom date ranges. Currently, the breakdown resets on the 1st of each month, making it impossible to audit past consumption patterns once the month ends. Audit Log Integration: A dedicated "AI Audit Log" or better filtering in the existing Automation Audit Log to specifically isolate AI-related consumption events. Why this is important: As a decision-maker, I cannot confidently purchase additional AI Credit packs or add-ons without understanding exactly how our current credits are being spent. Clear visibility is the bridge between a "trial" and a "paid" commitment. Better governance tools will help teams optimize their workflows and scale their AI usage responsibly.

I had no idea that my chat history was not saved. I've lost so much work because of this. Brain chat history should be fully preserved and searchable, not limited. As a power user, I lost valuable work (social media copy, business plans, creative iterations) when older chats disappear. Both ChatGPT and Claude retain full history. Additionally, Brain itself should be able to reference prior conversations for continuity. This is critical for users who collaborate iteratively with AI over time. Please let me know when this will be fixed.

When a AI Notetaker records calls, I would like the transcripts to be available to everyone in my team by default.

Description: When Brain gives follow-up suggestions at the end of a response, clicking one dismisses all the others. Often 2 or 3 of them are things I want done. Currently my workaround is to screenshot the suggestions, paste the image into the next message, and say "do all of these." Request: Let users select multiple follow-ups (checkboxes or shift-click) and submit them together as one prompt, rather than forcing a single choice that removes the rest.

My Claude is frequently running into errors using the clickup_get_custom_fields tool: one of our custom fields is >40KB (lots of really specific epic names) and the server is truncating that field at column 41,769. Would you consider increasing that limit? Alternatively, could you add an include_options: true|false param on the clickup_get_custom_fields tool so we can exclude if needed? Option lists are ~90% of that payload and the overwhelmingly common need is just the field ID. More details from Claude: Bug: clickup_get_custom_fields (with list_id or folder_id) and clickup_get_task (with include: ["custom_fields"]) return an SSE frame whose JSON payload is truncated mid-string. The client fails with: Failed to parse SSE message: Invalid JSON: EOF while parsing a string at line 1 column 41769 Deterministic — the identical call truncates at the identical column on every retry, across sessions and days. Different calls truncate at different offsets (41769 and 53706 observed), so it is not a fixed size cap. There is no partial result and no error object; the tool is simply unusable for these scopes. Smaller calls on the same connector succeed (space-scoped custom fields ~15KB, 100-task filter_tasks ~36KB, get_workspace_members ~25KB). Other remote MCP connectors in the same client return 290KB+ responses without issue, so this looks connector-side rather than a client or transport limit. Contributing factor: this space has large dropdowns — one Epic field with 93 options, Area with 32. List/folder scope stacks space-level fields plus list-level ones, which is where it tips over. Feature request: add a way to fetch field _identity_ without the option payloads — e.g. include_options: false, or a fields name filter on clickup_get_custom_fields. Dropdown options are the overwhelming majority of the bytes and most callers only need the field ID to write a value. This would sidestep the truncation entirely and cut response size by ~90% for the common case. Secondary: even with that, oversized responses should fail with a structured MCP error rather than a truncated JSON string, so clients can retry or degrade instead of hard-crashing on a parse error.