ForkOff – Orchestrate Your Claude Agents, Anytime, Anywhere

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Anthropic just launched Remote Control for Claude Code. It lets you control a coding session from your phone or browser. Cool idea, except it requires a $200/mo Max plan, supports one session at a time, has no auto-approve rules or hook management, and kills your session if the terminal closes or you lose network for 10 minutes. I built ForkOff because I kept coming back from skiing and biking to find my Claude Code sessions dead. I wanted to approve tool calls from my phone while I was out, not babysit a terminal. ForkOff is the open-source alternative: - Free (MIT licensed) - E2E encrypted — the relay server sees only opaque blobs - Auto-approve rules — configure which tools are safe, which need manual approval - Proper diff rendering on mobile, not raw terminal text - Sessions survive terminal close - Self-hostable relay, or --local flag for direct P2P (zero internet) - Multi-session support Stack: React Native + Expo (mobile), NestJS (relay), Node.js CLI that hooks into Claude Code's PreToolUse/PostToolUse lifecycle via the SDK. X25519 key exchange, XSalsa20-Poly1305 encryption. iOS beta is live on TestFlight. Android coming soon. We are looking forward to feedback, code contributions, and more! TestFlight: https://testflight.apple.com/join/dhh5FrN7 (Note: We are currently pending apple's review on the open-source version of the app expect the release on the above link within 24 hours till then the app config will show that you require an update) GitHub (CLI): https://github.com/Forkoff-app/forkoff-cli GitHub (Mobile): https://github.com/Forkoff-app/forkoff-react-native Website: https://forkoff.app

Visit product View on Hacker NewsFeb 25, 2026

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

89%89% 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: supports, ios · Missing: reddit linkedin, podcasting, created

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

43%43% 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, io · Missing: https docs, excited, just released

37%37% 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 · Strong signals: host, soon, calls · Missing: plus, platform, intuitive

33%33% 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

24%24% 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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