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Pocket Agent: run Claude, Cursor, Codex and more from your phone

Hacker News

Pocket Agent: run Claude, Cursor, Codex and more from your phone

Hi HN, I built Pocket Agent — a mobile-first interface for coding agents like Claude Code, Cursor, Codex, Gemini, and OpenCode. It lets you connect to your own dev environment (or cloud agents) and interact with them in real time from your phone. Pocket has two parts: • Pocket Server (open-source): lightweight server (Mac + Linux today, Windows soon) you run on your machine. It securely exposes your environment to Pocket. • Pocket App (beta): your mobile interface. You can: • Chat with agents (Claude, Cursor, Codex, Gemini, etc.) • Run and monitor terminal sessions in real time • Approve or deny file edits, searches, or commands • Launch and track cloud background agents • Manage multiple projects/sessions — all from your phone Traction in the first 24 hours: • 1,400+ unique visitors • 350+ beta signups • 130+ GitHub stars • Community already contributing: Linux support, Tailscale pairing, Claude Code auth integration Repo: https://github.com/yayasoumah/pocket-server Website: https://www.pocket-agent.xyz I’d love your feedback — especially if you’re building or using CLI agents. What would make you adopt and trust a mobile-first agent workspace?

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Actual performance

4points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agents, agent · Missing: macos, model, apple
99%99% 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
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
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 · Strong signals: interface, soon · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
38%38% 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
31%31% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat, real time · Missing: web3, crypto, cryptocurrency
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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