Danube – AI Tools Marketplace

Hacker News

Hey HN, I built Danube, a marketplace where AI agents can discover and execute tools, and where developers can publish and monetize them. I got tired of two things: giving my API keys directly to agents like OpenClaw (didn't feel secure), and having to re-setup all my MCP servers every time I switched between Cursor, Claude Code, and other tools. Danube stores your credentials securely. Your agent calls the tool and never sees the keys. And since it's one MCP connection, you set it up once and it works across all your clients. For devs who want to publish: you upload an OpenAPI spec or MCP server, optionally set pricing, and you're live. Agents can search and find your tools without users needing to manually configure anything. 100+ services work today. No signup required to browse. Would love to hear what tools you use most with AI agents. If anyone's interested in publishing a tool, happy to help get you set up.

Visit product View on Hacker NewsMar 24, 2026

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Did not reach leaderboard

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

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.

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

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users, calls · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

26%26% 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

22%22% predicted probability of success on Acquire.com, 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

21%21% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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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