ClawDaddy – Deploy OpenClaw by chatting with one on Telegram

Hacker News

ClawDaddy hosts OpenClaw AI agents, which you can set up and deploy by chatting with one on Telegram. I grew tired of the complicated OpenClaw setup process—Node, Docker, BotFather, gateway pairing, authentication configurations, and security patches. So I decided to let an agent manage all that for you. Each agent operates on its own server rather than a shared container. Try @clawdaddyrunbot on Telegram—your feedback is welcome.

Visit product View on Hacker NewsFeb 27, 2026

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

81%81% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

24%24% 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

21%21% 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 · Missing: plus, platform, intuitive

20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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