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REPL is the memory layer for multi-agent AI apps – Sherlog‑MCP

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REPL is the memory layer for multi-agent AI apps – Sherlog‑MCP

Hi all, I know the MCP fatigue is real but just wanted to share something I was working on and thought there might be some folks here that might be interested. Working on a Sherlog-MCP: Which is a MCP built around an ipython shell providing a persistent workspace for multiple ai agents to collaborate and work on tasks. One of the applications we are focusing on is bug investigations. Thanks!

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, mcp · Missing: mac, macos, cursor
95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
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Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: collaborate · Missing: web3, chat, crypto
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