Most security tooling for credentials answers one question: where is the secret stored? AI agent access control answers a different one: at the moment an AI agent acts, may it use this credential — here, now, for this action? As agents gain the ability to read files, run commands, call tools, and run in loops across many client workspaces, that moment of use becomes the real control point. The same pattern is increasingly called a credential broker for AI agents — a different name for the same layer. Because that broker acts at execution time rather than at storage time, it is sometimes named more precisely as a runtime credential broker: the moment-of-use decision, not the place secrets sit at rest.
A distinct layer — not storage, not a connector
Runtime access sits above two things people often confuse it with:
- →Not a vault. A vault stores and rotates secrets, then returns the value to the caller. Runtime access governs whether the caller may act at all — see agent access router vs. vault and why a secrets manager isn't enough.
- →Not just a connector. MCP and similar protocols connect an agent to a tool when one exists. Runtime access decides whether a given request is allowed for this tenant and performs it without exposing the key — see credential broker vs MCP authentication.
- →Not just authorizing an action. Deciding an action is allowed is only half the decision — the other half is routing it to the correct client account. An agent can be fully authorized to call a service and still reach the wrong client's account if nothing resolves the request to the right workspace-pinned credential first.
What secure AI agent access actually controls
A runtime access decision is made against the full shape of the request, not just "is this key valid":
- ✓Tenant / workspace — which client is this agent acting for?
- ✓Service & host — which API, on which allowed host?
- ✓Action — a fixed, approved verb, not arbitrary use of a raw key.
- ✓Result handling — redact the response and write a local audit.
How a request flows
Request → policy → broker → redacted result → audit
- 01
Agent request
The agent asks for an approved action or alias — not a raw key.
- 02
Policy & tenant check
Outloop checks project, tenant identity, and runtime policy before anything runs.
- 03
Local broker
On approval, the local broker uses the credential on the wire to perform the call.
- 04
Redacted result
The agent receives a sanitized, non-secret result. Raw values never enter its context.
- 05
Audit log
Every attempt is written to a redacted local audit — decision, tenant, service.
The agent never sees the credential. A wrong-tenant request is denied at the policy check, before any backend call.
Where Outloop fits
Outloop is a local-first runtime access layer for AI agents. Secrets stay in your existing backend; agents request approved actions, not raw keys; wrong-tenant calls are blocked by policy before any backend call; and every attempt is written to a redacted local audit. It is the access layer for the cases that matter most today — agent loops, API key management, and multi-client agencies.
