Users are actively exploring Notion's evolving capabilities (e.g., MCP, AI) and adapting it for complex, multi-database use cases, indicating a need for better guidance and feedback mechanisms to support advanced workflows.
Users are pushing Notion beyond simple note-taking into complex relational database structures (e.g., Recipes, Ingredients, Clients) and are unaware of new features like MCP, highlighting a gap in feature discovery and user education.
Snapshot context
What makes this snapshot distinct
This snapshot is distinct because it combines reddit + g2 evidence within last 15 days, with 4 quote-backed signals around Close The Feedback Loop is a recurring product feedback theme. It also references related products such as close the feedback loop.
Most important finding
Users are pushing Notion beyond simple note-taking into complex relational database structures (e.g., Recipes, Ingredients, Clients) and are unaware of new features like MCP, highlighting a gap in feature discovery and user education.
Suggested focus
Monitor discussions around Notion's AI and MCP features, as well as advanced database usage, to identify where users struggle and where feedback loops can be improved.
AI feedback clusters
Feature Discovery and Adoption
Users are unaware of new Notion features like MCP and AI, and are still using manual processes, indicating a discovery gap.
βi'll be honest, i had no idea notion had an mcp. i used to use notion a lot back before agents were a thing, when they first dropped Notion AI you can pay extra for. i was still doing everything manual. i took a huge hiatus and came back to notion having aβ
Complex Workflow Setup
Users need to design multi-database architectures for specialized use cases, which requires significant upfront effort and expertise.
βThe one design decision that matters here: make Ingredients its own database instead of a multi-select on the recipe. Three databases, related to each other: Recipes, Ingredients, Clients. On Ingredients you put the allergen tags (nuts, dairy, gluten,β
AI root-cause hypothesis
Notion's rapid feature expansion may outpace user awareness and onboarding, leading to underutilization of new capabilities and frustration when users discover limitations in their existing setups.
Product implications
Enhance in-product tutorials and contextual tips for advanced features like MCP and AI, and provide templates for complex database structures to reduce friction.
Position as a more guided alternative with built-in best practices for complex workflows, addressing the learning curve Notion users face.
Focus on niche solutions that simplify specific workflows (e.g., recipe management) with pre-configured databases and clear feedback loops.
Source evidence supporting this signal
βYea I mean I use it for everything now, project management, a database of manuals for all my hardware and software, glossaries of terms for certs, etc. but it really depends on what you want and how you want it.β
βi'll be honest, i had no idea notion had an mcp. i used to use notion a lot back before agents were a thing, when they first dropped Notion AI you can pay extra for. i was still doing everything manual. i took a huge hiatus and came back to notion having aβ
βThe one design decision that matters here: make Ingredients its own database instead of a multi-select on the recipe. Three databases, related to each other: Recipes, Ingredients, Clients. On Ingredients you put the allergen tags (nuts, dairy, gluten,β
βWhat I like best about Notion is how it combines notes, documentation, project management, and collaboration in one flexible workspace. Itβs simple enough for everyday use while being powerful enough to organize complex projects and workflows. The only thingβclose the feedback loopΒ· g2