A

A Medical Research Agent Built with BioMCP and Haystack

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A Medical Research Agent Built with BioMCP and Haystack

I created a simple app to explore how Agents & MCP can help with medical research. It connects to ClinicalTrials.gov, PubMed/PubTator, and MyVariant.info using the BioMCP Server( https://github.com/genomoncology/biomcp ), and uses Haystack( https://github.com/deepset-ai/haystack ) as the MCP Client. The idea is to let users ask natural-language questions like: - Are there new studies on treating acne? - What trials exist for migraine prevention? - Show me trials for managing hay fever symptoms - What are some ongoing trails for never-smokers with lung cancer? If you’re curious, here are the links: - MedOryx App: https://med-oryx.streamlit.app - MedOryx GitHub: https://github.com/oryx1729/med-oryx Would love any feedback or thoughts.

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, mcp · Missing: mac, macos, cursor
82%82% 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 · Strong signals: users · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting
39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, ide, io · Missing: https docs, excited, just released
35%35% 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
19%19% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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