Stm32-MCP – let AI build, flash, & communicate with hardware

Hacker News

Been working on this one for a little bit now. I do mostly embedded work. The big friction with Claude Code and that kind of work was stopping him from trying to build and flash my hardware, because he couldn't reliably, and having to relay results back to him manually. We wrote stm32-mcp to close that loop and let Claude go to town. One of my fav features here is sequencing. You can define a list of commands, expected responses, timeouts, delays, etc to get the agent's timing out of the way. This has pretty much revolutionized how I develop hardware... If you try it out, get Claude to explain what it can do! and make sure you treat it like something insane that can break all your stuff.

Visit product View on Hacker NewsMar 30, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, claude, mcp · Missing: mac, agents, macos

98%98% 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.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

33%33% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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