PhonePi MCP: Connecting my phone to AI assistants via MCP

Hacker News

Hi HN, I wanted to share an early version of something I am working on. PhonePi MCP is an open source MCP server + companion Android app (iOS coming soon) that lets you connect your phone to AI assistants/apps running on your Desktop PC/Mac (such as Cursor, Claude Desktop or any other client that implements MCP!) and automate tasks such as: - send SMSs, place phone calls via your AI assistant - manage contacts with AI assistance - copy things to your phone's clipboard as you interact with your favourite AI app - let AI keep you updated on long running tasks via notifications as and when milestones are reached and long running tasks complete - store AI artifacts such as drafts, todos etc in your phone's memory and triage them with AI assistance. - set timers + find phone functionality and more! There are currently 23+ tools exposed via the MCP server and app combination which can be combined to power-up some nifty personal productivity workflows. Do check out the demo video on the website when you find some time (watch it at 2x to save time) and if you're interested in trying it out, there are a few Play store coupons on the site. I look forward to any feedback this amazing community may have for this early work!

Visit product View on Hacker NewsMar 29, 2025

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

93%93% 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: ios · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, month

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

AppSumoMay struggle as an AppSumo deal · Strong signals: soon, calls · Missing: plus, platform, intuitive

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

25%25% 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.

Correct prediction on native model

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