Cline – Open-Source VS Code AI Coding Agent with a New MCP Marketplace

Hacker News

Hey HN! My name is Nick, and I lead Product Marketing at Cline. Over the past few weeks, we’ve been hard at work on a major update for Cline ( https://github.com/cline/cline ) and would love your feedback. For those who haven’t heard of us, Cline is an open-source AI coding agent extension for VS Code (we just hit 30k stars on GitHub). It’s model agnostic and works on a bring-your-own-key API model, enabling Cline to read, write, and edit your files so you can build and maintain complex software faster than ever before. A couple of months back, we introduced MCP servers ( https://modelcontextprotocol.io/introduction ) to Cline, allowing users to integrate new tools powered by Anthropic’s Model Context Protocol. While we’ve seen some really cool uses—from perplexity research to Notion integration—we noticed that many users find the concept of “MCP” a bit abstract. That’s why we just launched the MCP Marketplace—a one-click install suite where you can easily add a variety of new tools to Cline. We believe this will lower the barrier to entry and help you better understand and leverage MCP servers. (Tip: The perplexity MCP is my favorite!) I’d love to hear from both long-time Cline users and newcomers. Your feedback will help shape our content and support efforts for adopting MCP servers in Cline. Here are a few questions that would really help us improve Cline: 1. What is your current understanding of MCP servers? - How do you think they work and what benefits do you expect? 2. Have you tried using MCP servers in Cline? - If yes, what was your experience like? If not, what’s holding you back? 3. Where do you see gaps in understanding or setup with MCP servers? - Are there particular aspects (documentation, installation, use cases) that feel unclear or challenging? 4. What kind of content or support would help you adopt MCP servers more confidently? - For example, would detailed tutorials, videos, or troubleshooting guides be useful? Looking forward to your thoughts and questions—thanks for taking the time to help us build a better tool! Thank you! -Nick & the Cline team

Visit product View on Hacker NewsFeb 19, 2025

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

99%99% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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Hacker NewsMay not resonate with HN audience · Strong signals: ide, 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.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · 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 · Strong signals: arr · Missing: mrr, revenue, profit

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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