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Netcat-chat – a simple, colorful chat server you can use with netcat
Hacker NewsNetcat-chat – a simple, colorful chat server you can use with netcat
i built a chat server that you can connect to using netcat or telnet. it's written in python and supports multiple users, colorful messages, and custom nicknames. it's a fun way to chat with friends or colleagues without needing a special client. features: connect using just netcat, colorful output (gray for system, pink for your messages), change your nickname on the fly, see who's online. repo: https://github.com/oeo/netcat-chat
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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, using · Missing: mac, agents, macos39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue12%12% 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 · Missing: web3, crypto, cryptocurrency2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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