Gunbot – self-hosted trading bot (lifetime license, ETF, CEX and DeFi)

Hacker News

Hi HN, I’ve been building and maintaining *Gunbot*, a trading-automation engine you install on your own hardware (or a lightweight VPS). Most bots in this space are SaaS products that bill you every month; we believe in a *lifetime-license model* instead—pay once, keep it forever, no feature gating later. Why it might interest builders and algo-traders here: • *Runs locally* – execution, logs, and keys remain under your control. • *CEX + DeFi ready* – plugs into Binance, Coinbase, etc., but also dYdX, PancakeSwap, and Hyperliquid. • *Hackable strategy layer* – drop your own JavaScript snippets to shape entry, exit, and risk logic. • *One-time cost* – usually cheaper than a single year of the common $30-$100/mo bots. I’d love feedback on: 1. Any blockers you see in running a self-hosted bot safely? 2. Which additional DeFi venues or risk-management tools would make you trust it more? 3. Whether the lifetime model resonates with you compared to perpetual subscriptions. Docs, pricing tiers, and full changelog are on the site. Happy to answer questions or share implementation details in the thread. — Gunbot maintainer

Visit product View on Hacker NewsMay 23, 2025

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, single · Missing: mac, agents, macos

50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host, builder · Missing: plus, platform, intuitive

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas, subscription · Missing: arr, mrr, revenue

28%28% 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.

Incorrect prediction on native model

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