Canny verdict · build Solution request

ClickUp extension for AI-filtered chat and inbox messages

Built for AI/automation engineers building agentic systems on top of ClickUp who need to distinguish seen vs. unseen communications..

“The ClickUp MCP currently has no way to surface whether a chat message or inbox notification has been read. When building AI agents or automations on top of Cli…”

The receipts — real demand

“The ClickUp MCP currently has no way to surface whether a chat message or inbox notification has been read. When building AI agents or automations on top of ClickUp chat, this is a significant gap — without read/unread state, there's no reliable way to filter "what the user hasn't seen yet."”

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6.2 / 10 · demand score
Pain 8
Willingness to pay 5
Feasibility 6
Specificity 9
Audience 6
Competition 6

Why this is a gap

Surfaced from a high-intensity complaint with clear willingness to pay and a specific, reachable audience.

The market

AI engineers building agentic systems on ClickUp need read-state visibility for reliable automation logic. No search volume indicates this is a niche problem within a niche (ClickUp AI automation builders), not a broad category.

Competition & the opening

Crowded market · 6/10 vs ClickUp

ClickUp's native MCP and API documentation already cover basic chat retrieval. The gap is specifically in the read-state field, which is a data model gap in the MCP, not a product gap that competitors address differently.

What's hard to build

ClickUp's MCP may not expose read-state in its schema at all, requiring either a direct API request to undocumented endpoints or a workaround like timestamp tracking. The 6/10 feasibility suggests the technical barrier is moderate—likely a reverse-engineering or API limitation issue rather than infrastructure complexity.

Why now

ClickUp MCP adoption is rising for AI agents but missing read/unread state blocks intelligent filtering and automation workflows.

How you'd monetize

$29-99/mo SaaS API or MCP service