MCP² (Mcpsq) – A MCP Server to Discover and Install Other MCP Servers

Hacker News

Hi HN, I recently built something called MCP² (mcpsq) – a "MCP of MCPs", or a meta-MCP server. What is it? It’s a management layer for the Model Context Protocol (MCP) ecosystem. By installing mcpsq in an MCP-compatible client (like Cursor), you can directly chat with your AI agent to help you find, install, and manage other MCP servers — using natural language. Site: https://mcpsq.xyz GitHub: https://github.com/xinbenlv/mcpsq If you're an MCP server developer We're opening up early-stage server registration. You can submit your server by sending a Pull Request — it's the easiest way to be discovered by others in the ecosystem. If you're an MCP user This project aims to provide the most MCP-native way to install MCP servers — directly via AI chat, without needing to fiddle with configs manually. Currently supports Cursor, with Claude and ChatGPT support coming soon. Would love your feedback or contributions — and a on GitHub would be awesome! Thanks! Victor (github.com/xinbenlv)

Visit product View on Hacker NewsMay 28, 2025

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

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.

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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

16%16% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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