Why agents need a control plane
AI agents do not behave like normal apps or human users. They can chain tool calls, infer next steps, run commands, modify files, call APIs, and act faster than manual review can keep up. Traditional identity tools can tell who logged in. A control plane for agents must also decide whether a specific action is allowed at the moment it happens.
The core objects
Credential brokering
Agents should not inherit a developer's full shell, cloud, or SaaS permissions. A credential broker issues short-lived grants scoped to a task, repo, resource, action, and environment. Production and destructive actions should default to deny or require approval.
MCP and tool authorization
Tool calls are where agents become operators. Every MCP or SaaS tool call should be authenticated as an agent session, checked against policy, redacted if sensitive, approval-gated when high risk, and logged with outcome evidence.
Runtime enforcement
The first enforcement point is local: files, shell commands, network calls, Git operations, and secrets. The same decision model can extend to CI/CD runners, deploy systems, cloud APIs, databases, package registries, and SaaS connectors.
Audit and revocation
Security teams need to answer what the agent saw, what it changed, which policies fired, which credentials were used, who approved the action, and how access was revoked. Audit logs should be searchable, exportable, and useful for incident response and compliance.