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OpenChat – Syncing conversations across AI providers

Hacker News

OpenChat – Syncing conversations across AI providers

I decided to build OpenChat to solve a problem myself and others have faced. Conversations with AI are currently split across different providers. OpenChat automatically stores conversations in the browser locally. You can then reference the conversations in your coding agents via an MCP server. E.g. you can do deep research on the web, then reference it in your coding session.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, mcp · Missing: mac, macos, cursor
80%80% 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
38%38% 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
33%33% 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 · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
31%31% 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
21%21% 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, cryptocurrency
9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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