AI agents need OAuth tokens for user accounts, but most frameworks store them in plaintext config files. Cred is open-source credential delegation middleware. The user consents once. Cred encrypts the refresh token (AES-256-GCM) and never returns it. Agents get short-lived tokens on demand. Every delegation produces a cryptographic audit receipt. We also ship CredX: a single-command encrypted credential store for agents who don't need the full SDK. Self-hosted. Apache 2.0. Zero cloud dependency.
There's no standard credential layer for AI agents, so I built one. Cred sits between the agent and a user's accounts. The user consents once. The agent gets short-lived tokens on demand. Refresh tokens stay encrypted in a vault and are never returned.
The whole thing is open-source and self-hosted. No cloud dependency, no vendor lock-in. The standalone packages (@credninja/oauth + @credninja/vault) give you full local control. And if even that's more than you need, CredX (github.com/cred-ninja/credx) is the minimal version: one command, encrypted vault, auto-refresh, done.
Happy to answer anything about the architecture, security model, or roadmap!
About Cred on Product Hunt
“OAuth credential delegation for AI agents”
Cred launched on Product Hunt on April 9th, 2026 and earned 93 upvotes and 3 comments, placing #33 on the daily leaderboard. AI agents need OAuth tokens for user accounts, but most frameworks store them in plaintext config files. Cred is open-source credential delegation middleware. The user consents once. Cred encrypts the refresh token (AES-256-GCM) and never returns it. Agents get short-lived tokens on demand. Every delegation produces a cryptographic audit receipt. We also ship CredX: a single-command encrypted credential store for agents who don't need the full SDK. Self-hosted. Apache 2.0. Zero cloud dependency.
On the analytics side, Cred competes within Developer Tools, Artificial Intelligence, GitHub and Alpha — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Cred performed against the three products that launched closest to it on the same day.
Who hunted Cred?
Cred was hunted by Kieran Sweeney. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Cred including community comment highlights and product details, visit the product overview.
Kieran Sweeney
Hi PH, I'm Kieran, the builder behind Cred.
There's no standard credential layer for AI agents, so I built one. Cred sits between the agent and a user's accounts. The user consents once. The agent gets short-lived tokens on demand. Refresh tokens stay encrypted in a vault and are never returned.
The whole thing is open-source and self-hosted. No cloud dependency, no vendor lock-in. The standalone packages (@credninja/oauth + @credninja/vault) give you full local control. And if even that's more than you need, CredX (github.com/cred-ninja/credx) is the minimal version: one command, encrypted vault, auto-refresh, done.
Happy to answer anything about the architecture, security model, or roadmap!