A Multi User Multi Task Board MCP Server

Hacker News

I built a simple multi user, multi board, Task/Kanban MCP server. I have been looking for something like this to manage development agents, but I wasn't seeing anything that felt like what I wanted. So I set down and decided to vibe code an alternative. While it was an experiment at first I have been using it daily for my personal development projects and I really think there are others who might be looking for exactly this. It's 100% a WIP, but it is also very usable. I have a demo instance running at https://mootasks.dev . If you find this interesting I'd appreciate a star. This is really the first thing I built that I felt would be of interest to others. The readme explains it, but if you have docker you can get this running in a couple minutes. It's helped my workflow a lot and I plan on continuing to add features / improve it.

Visit product View on Hacker NewsApr 29, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, mcp · Missing: mac, macos, cursor

88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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