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Almanac MCP, turn Claude Code into a Deep Research agent

Hacker News

Almanac MCP, turn Claude Code into a Deep Research agent

I am Rohan, and I have grown really frustrated with CC's search and read tools. They use Haiku to summarise all the search results, so it is really slow and often ends up being very lossy. I built this MCP that you can install into your coding agents so they can actually access the web properly. Right now it can: - search the general web - search Reddit - read and scrape basically any webpage Install it: npx openalmanac setup The MCP is completely free to use. We have also built a central store where you can contribute things you learned while exploring. If you find something useful, you can contribute it to the encyclopedia we're building at Almanac using the same MCP.

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Actual performance

14points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, claude · Missing: mac, macos, cursor
97%97% 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 NewsMay not resonate with HN audience · Missing: https docs, excited, just released
46%46% 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
46%46% 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
33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
27%27% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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