Authorize MCP tool calls without giving agents the credentials

Hacker News

Hey HN, Adam here. We built a small MCP example around a single problem: How do you let an agent use a tool that needs credentials without giving the credentials to the agent? The demo has two tools. One is open. One is protected. When the agent calls the protected tool, Keydris checks the policy first: ALLOW → run the tool REJECT → stop The credential stays on the server. The agent never sees it. We do the check through a small middleware on the MCP server called the KIT Reader. Repo: https://github.com/keydrisLabs/mcp-auth-keydris-template We're early. If you're building with MCP, Claude Code or Codex, I'd love to know how you're handling this today and where you think this approach breaks. We support other elements like integrations etc but would love your feedback

Visit product View on Hacker NewsSep 14, 2026

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

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

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

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

35%35% 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

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

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

28%28% 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

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

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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