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I've just released my new open source MCP server called mcpcap

Hacker News

I've just released my new open source MCP server called mcpcap

mcpcap is a modular Python MCP (Model Context Protocol) Server for analyzing PCAP files. mcpcap enables LLMs to read and analyze network PCAP's with protocol-specific analysis tools that accept local files or remote URLs as parameters. Landing page: https://mcpcap.ai Docs: https://docs.mcpcap.ai GitHub: https://github.com/mcpcap/mcpcap

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Actual performance

1points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, mcp, new · Missing: mac, agents, macos
84%84% 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.
Hacker NewsStrong engagement from HN community · Strong signals: just released, open source · Missing: https docs, excited, exist
64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: para · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: para · Missing: supports, reddit linkedin, podcasting
30%30% 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
15%15% 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
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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