MCP Defender – OSS AI Firewall for Protecting MCP in Cursor/Claude etc

Hacker News

Hi HN, MCP Defender is an open source desktop app that automatically proxies your MCP traffic in AI apps like Cursor, Claude, Windsurf and VSCode. It then scans all requests and responses between the apps and the MCP tools they call. If it detects anything malicious, it alerts you and lets you allow or block the tool call. While the threat landscape of MCP is still being actively researched, there are dangerous things that MCP Defender can block today. For example, a developer asks Cursor to fix a Github issue with an attached crash log. However, the Github issue was created by an attacker who included secret instructions buried in the crash log. These instructions tell Cursor to send the developer’s SSH keys to a server the attacker controls. MCP Defender detects these malicious instructions and alerts the developer who otherwise may not be careful in running tool calls. The scanning is currently done via an LLM and checks for things like prompt injection, credential theft (ssh keys, tokens) and arbitrary code execution. You can use an MCP Defender account or provide your own API keys for LLM providers to perform the scanning. Currently we’ve published a beta Mac build and we’ll soon publish builds for Windows and Linux as well. Any feedback would be greatly appreciated. Thanks!

Visit product View on Hacker NewsMay 29, 2025

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

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: apps · Missing: mobile apps, ios, personal

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

22%22% 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

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

Incorrect prediction on native model

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