Family Tree Maker

Hacker News

Family Tree Maker

I'm writing a book of my family's history and I want to add good looking trees for each family. I started building them by hand but it's a lot of work to design and maintain. So I built this "Family Tree Maker". You can use the built-in form and download the image, as well as save the URL to come back to your tree later. It also works as an API and MCP server, for use with AI like ChatGPT or Claude. I'm using this to automate building this trees: I ask Claude to take the FamilySearch data and build the tree image of a single family. The website is free and the code is open-source on GitHub: https://github.com/mnapoli/family-tree-maker

Visit product View on Hacker NewsApr 21, 2026

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

83%83% 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 · Missing: mobile apps, ios, personal

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

53%53% 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

36%36% predicted probability of success on AppSumo, 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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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