MCP-Linker – 6MB GUI for Managing MCP Servers (Tauri)

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GitHub: https://github.com/milisp/mcp-linker Releases: https://github.com/milisp/mcp-linker/releases MCP-Linker is a Tauri-based cross-platform GUI app (~6MB) to manage MCP servers used in Claude Desktop, Cursor, and other AI tooling environments. Features: - Add/manage custom MCP servers - Favorite and recently used server tracking - Native builds for macOS and Windows - Offline-first, fast startup, no bloat Built with Tauri for small footprint and native performance. Fully open-source. Feedback and contributions welcome!

Visit product View on Hacker NewsApr 29, 2025

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

92%92% 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 · Missing: mobile apps, ios, personal

45%45% 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.

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

34%34% 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

29%29% 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

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

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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