Open-source macOS app to install and manage MCPs

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I've been experimenting more with MCPs and felt like the process around discovering, installing and managing them was a lot harder than I expected. So I built a quick native macOS app to help with that and am now open sourcing it. Repo is here: https://github.com/jshchnz/MyMCP I've only really tested on Claude Code and Cursor, but it should support other clients like Codex, Gemini, VS Code, etc.

Visit product View on Hacker NewsDec 30, 2025

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

95%95% 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 · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

22%22% 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

17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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