Feature Requests

I’d love to see a feature in ClickUp AI similar to ChatGPT’s “Custom Instructions.” Instead of re-selecting a saved prompt every time, I want to define my AI style, tone, goals, and contextual preferences once—and have them automatically applied across all interactions with ClickUp Brain and AI Agents (in tasks, chat, etc.). Why this matters: • It’s key for creative brainstorming and maintaining consistent tone across work. • Saves time from having to reapply prompts. • Makes AI truly feel like an extension of my workflow and voice. Bonus feature idea: Allow workspaces to upload contextual documents (PDFs, strategy docs, style guides) that AI can reference persistently.

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.

It'd be dope if clickup AI would support https://modelcontextprotocol.io/ . With that its agent could instantly integrate with a ton of tools without you having to do first party integrations in the first place. Some tools like cursor.ai just allow you to paste in an MCP link and bam, you have it in your agent. Support this ONE thing and save time integrating all the others. Let your users do the job and give them the power to integrate properly.

It would be extremely valuable for ClickUp AI Brain to allow web search capabilities regardless of which AI model is selected. Currently, the ability to retrieve and reference information from the web appears to be limited to the "Max" model. As a result, users must choose between using their preferred AI model and accessing current information from the internet. Many users select different models for specific strengths such as reasoning, writing style, speed, creativity, technical expertise, or cost efficiency. Restricting web access to a single model limits flexibility and can prevent users from leveraging the best model for a given task. Example Use Cases: Researching industry trends while using a preferred reasoning model Gathering current market information while drafting a proposal Referencing recent product updates or competitor activity Creating content informed by current events and public information Conducting research without needing to switch models Benefits: Provides a more consistent AI experience across models Allows users to choose the best model for the task without sacrificing web access Improves research quality and accuracy Reduces the need to switch between models or external AI tools Increases flexibility and user satisfaction Strengthens ClickUp AI Brain as a centralized productivity and research platform Ideal Functionality: Web search available as a toggle regardless of selected AI model Ability to enable or disable web access per prompt Clear citation or source references when web content is used Consistent user experience across supported AI models Administrative controls for organizations that wish to limit web access Today, users who require current information from the internet are often forced to use a specific model rather than the model best suited for their task. Enabling web access across all supported AI models would provide greater flexibility while delivering a more consistent and powerful AI experience.

Either integrating with the AI scheduler Addie, or creating your own automatic scheduling AI that decides what order you should do things in based on priority, due date, etc

We would like to request enhanced administrative controls and visibility for AI credit usage within ClickUp. AI Credit Usage Dashboard Provide an admin-level dashboard that displays: Total AI credits available to the workspace. Remaining AI credits for the current billing period. AI credit consumption per user. Historical usage trends by user and by month. A ranking or breakdown showing which users are consuming the most and least AI credits. Visibility into which AI features are consuming credits (e.g., AI Chat, AI Agents, AI Automations, AI Fields, Image Generation, etc.). This would help administrators monitor adoption, identify heavy users, and forecast future AI credit requirements. Per-User AI Credit Allocation Allow workspace administrators to assign custom monthly AI credit limits on a per-user basis. For example: User 1: 1,000 AI credits per month User 2 (Creative/Marketing): 10,000 AI credits per month User 3 (Project Manager): 2,500 AI credits per month This would enable organizations to allocate resources based on job function and business needs rather than applying the same allowance to all users. Shared Pool Management If a workspace receives a pooled allocation of AI credits (for example, 70 users × 5,000 credits = 350,000 AI credits per month), provide administrators with the ability to: View the total shared credit pool. Allocate credits from the pool to specific users. Reallocate unused credits between users. Reserve credits for specific departments or teams. Track how much of the pool has been consumed and how much remains. Dynamic Credit Adjustments During the Billing Cycle Allow administrators to increase or decrease a user's AI credit allocation at any time during the month. Example: User 1 is assigned 1,000 credits per month. User 1 reaches the limit 10 days before month-end. The administrator decides to grant an additional 2,000 credits. In this scenario, the additional credits should be deducted from the workspace's remaining shared credit pool, provided sufficient credits are available. This would give organizations flexibility to support users with temporary increases in AI usage without requiring plan changes or manual intervention from ClickUp support. Business Value These capabilities would provide organizations with: Better AI cost governance. Improved budget forecasting. Fair and role-based AI resource allocation. Increased visibility into AI adoption and usage patterns. Greater administrative control over pooled AI credit consumption. This functionality would be particularly valuable for larger workspaces where AI usage requirements vary significantly between departments and individual users.

The new Brain capability to generate and publish HTML artifacts (slide decks, pages, etc.) on run.clickup.ai is genuinely game-changing. It bridges the gap between ideation and polished output in a way no other project management tool does. However, the current editing workflow requires Brain to regenerate the entire artifact on every revision, which becomes painfully slow and error-prone for larger decks (15+ slides). In many cases the generation simply fails mid-way, forcing users to start over or abandon the edit entirely. The fix feels straightforward: allow users to target a specific slide or section for editing rather than reprocessing the whole file. Most real-world edits are surgical (swap a headline, tweak one chart, adjust copy on slide 9) not structural. If Brain could scope its regeneration to just the selected section, it would dramatically reduce latency, eliminate most timeout/error issues, and make iterative refinement actually viable. This single improvement would make ClickUp the obvious first choice for enterprise slide creation, no Canva or Google Slides detour needed.

It would greatly improve productivity if AI models in ClickUp could remember my conversation preferences—such as preferred response format, tone, and level of detail—across sessions. This would save time by eliminating the need to repeat instructions and ensure a more personalized, consistent AI experience for ongoing projects.

I would like to be able to have my Super Agent create a folder and an associated list. Today it can only create a lists.

Right now, ClickUp Super Agents can only perform direct actions on a small set of apps like ClickUp, Gmail, Google Calendar, and Slack. In practice, a large part of how we use Super Agents in our company is producing deliverables such as creating Google Sheets for execution plans, generating structured reports (sometimes in HTML format), producing documents, and preparing presentations (Google Slides/PowerPoint). Because these tools are not available, the agent output usually comes as plain text or code, and teams then have to manually copy it into a sheet or file, format it, and save or share it separately. This manual step is time-consuming, increases the chance of mistakes, and breaks the end-to-end experience inside ClickUp. For example, our Social Media team uses an agent to generate an execution plan, but they still need to manually move the output into Google Sheets each time, or each person has to convert and save the output as a file on their own. If ClickUp added tools to the Super Agent toolset for directly creating and editing Google Sheets, Google Docs, and Google Slides (and later other common productivity tools), this large category of day-to-day work could be completed without leaving ClickUp. This would significantly increase the value of Super Agents by turning outputs from “generated text” into “ready-to-use files and documents.” It would also reduce dependency on external tools for everyday workflows and help ClickUp become a more complete hub for creating, maintaining, and updating operational deliverables directly within the platform.