MCP Manager – Open-Source CLI to Manage Your MCP Servers

Hacker News

Hi HN! I'm Noah, an ordinary guy that got really interested in MCP about a month ago when I downloaded Cursor. It's been super exciting to see companies around the world launch their own MCP servers empowering AI to do more. Unfortunately, I got a bit overwhelmed setting up MCP servers across my clients like Claude Desktop, Cursor, and Claude Code, so I figured I'd take a shot at building an open-source tool to help others and myself! So yeah, I built a CLI tool that enables you to quickly get MCP servers from the Web integrated with your clients like Cursor and Claude Desktop. You can use the built-in MCP servers I've defined like Playwright, Github, etc and add your own configurations! Feel free to support me too. PRs are welcome! Thanks for reading this and have a great day!

Visit product View on Hacker NewsApr 23, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, 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: month · Missing: mobile apps, ios, personal

67%67% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

62%62% 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: io · Missing: https docs, excited, just released

42%42% 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

30%30% 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

18%18% 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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