I built a tool to generate MCP configurations for your servers

Hacker News

I’ve been working with MCP servers recently and got tired of writing configuration snippets for each client by hand. To make this easier, I built a small open-source tool https://mcp-config-generator.koladev.xyz/ It generates ready-to-use MCP configs you can drop into your README or documentation. Supported clients: - Remote servers: Cursor, Claude Desktop, VS Code, Continue, AnythingLLM, Qodo Gen, Kiro, Opencode, Gemini CLI - npm packages: Same list as above - Local scripts: Cursor + Claude Desktop It’s a simple idea, but I found it saving time. Feedback and suggestions are welcome. GitHub link: https://github.com/koladev32/mcp-config-generator

Visit product View on Hacker NewsSep 24, 2025

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

87%87% 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.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

41%41% 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: ide, io · Missing: https docs, excited, just released

25%25% 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

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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