Cordon – Security gateway for MCP tool calls with HITL approvals

Hacker News

MCP lets LLMs call real tools, databases, file systems, APIs. The spec has no security model. An agent is either off or full admin, and "trust the model" is the current answer. Cordon is an open source MCP gateway. It's a transparent proxy that sits between your LLM client and your MCP servers. Every tool call flows through it. You define policies per tool: allow, block, approve, read only, log only. The piece I haven't seen elsewhere is synchronous human-in-the-loop approvals. When a tool call hits an "approve" policy, the agent pauses and I get a terminal prompt (or a Slack Block Kit message) with the exact args. I approve or deny. The agent resumes. Every decision is logged. Install: `npx cordon-cli init` auto-patches your Claude Desktop config in about two minutes. Works with Claude Desktop, Claude Code, Cursor, Windsurf, and any stdio MCP client. Open source, MIT. Published to the official MCP registry as io.github.marras0914/cordon. There's also a hosted dashboard for centralized audit logs, but the gateway runs local and the CLI is fully offline. Happy to answer questions about the threat model, why I built it as a proxy vs. a client-side wrapper, or how write-detection works without me enumerating every dangerous tool name. GitHub: https://github.com/marras0914/cordon Writeup with config examples: https://dev.to/marras0914/mcp-has-no-security-model-heres-ho... Approval flow demo: https://i.imgur.com/nDAVxqN.gif

Visit product View on Hacker NewsApr 28, 2026

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

95%95% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on AppSumo, 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

32%32% 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 · Strong signals: arr · Missing: mrr, revenue, profit

19%19% 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.

Correct prediction on native model

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