Understanding Permissions in Queue

Learn how permissions work in Queue and how to give agents access to the tools they need—without compromising security.

As AI agents become more capable, permissions become increasingly important.

Agents can read repositories, interact with APIs, update tickets, access documentation, and automate workflows across multiple systems. While this flexibility is powerful, it also means teams need clear control over what agents can and cannot do.

Queue's permission system is designed to give organizations that control.

Why permissions matter

An AI agent is only as powerful as the tools it can access.

Without permissions, agents can't interact with your systems. With too many permissions, agents may have access to resources they don't actually need.

The goal is simple: give every agent the minimum access required to complete its work.

This approach improves security, reduces risk, and makes agent behavior easier to understand.

Agent permissions

Every agent in Queue operates with its own set of permissions.

These permissions determine which integrations, tools, repositories, and resources are available during execution.

For example, a documentation agent may only need access to your knowledge base, while a development agent may require access to GitHub, CI systems, and issue tracking tools.

By configuring permissions at the agent level, teams can create specialized agents with clearly defined responsibilities.

Workspace permissions

Workspace permissions control what team members can see and manage inside Queue.

Administrators can manage integrations, create agents, configure workflows, and control access across the organization.

This allows teams to maintain oversight while ensuring users only have access to the resources relevant to their role.

Integration permissions

When connecting external services, Queue only requests the permissions necessary for the configured workflow.

Teams can review connected integrations, manage access, and revoke permissions directly from the workspace settings.

This provides visibility into how agents interact with external systems and helps maintain a strong security posture as automation expands.

Best practices

When configuring permissions, start small.

Give agents access to the minimum set of tools required for their workflow. As use cases evolve, permissions can always be expanded later.

It's also a good idea to separate responsibilities across multiple agents rather than creating a single agent with broad access to every system.

Smaller permission scopes make workflows easier to audit, maintain, and trust.

Building with confidence

Permissions are one of the most important foundations of any AI platform.

They help ensure agents can operate effectively while maintaining the security, visibility, and governance organizations expect.

By carefully controlling access to tools, integrations, and resources, teams can deploy automation confidently and scale adoption without sacrificing oversight.

The most powerful agents aren't the ones with access to everything.

They're the ones with access to exactly what they need.