Authorize agent-to-agent communication with Cerbos
Control which agents can communicate, what capabilities they can share, and what data flows between them with policy-driven authorization powered by Cerbos.
Inter-agent authorization
Control which agents can communicate and what capabilities they can share through fine-grained Cerbos policies
Task delegation control
Authorize task delegation between agents based on user identity, agent roles, and task type at runtime
Audit every interaction
Every agent-to-agent authorization decision is logged with full context, giving you a complete audit trail of multi-agent workflows
How Cerbos works with Agent2Agent Protocol
AI agents and tools introduce a new class of authorization challenges. They act on behalf of users, access sensitive data, and chain operations, all of which need fine-grained access control.
Cerbos provides policy-driven authorization that controls what AI systems can do, which data they can access, and on whose behalf. Policies are written in human-readable YAML and evaluated at request time.
With Cerbos and Agent2Agent Protocol, you get guardrails that scale with your AI adoption, centrally managed policies, full audit trails, and sub-millisecond decision times that don't slow down agent workflows.
How Cerbos authorizes Agent2Agent interactions
- Define policies for agent communication, Write YAML policies that specify which agents can communicate with each other and what task types can be delegated, based on user identity and context.
- Source agent requests authorization, Before sending a task to a remote agent via A2A, the source agent sends the user context, target agent, and task type to the Cerbos PDP.
- Cerbos evaluates the inter-agent request, The PDP applies fine-grained rules considering the requesting user, source agent capabilities, target agent, and the nature of the delegated task.
- Task proceeds or is blocked, Cerbos returns an allow or deny decision. The orchestration layer enforces it, with every decision logged for audit.
FAQ
How does Cerbos authorize Agent2Agent interactions?
When one agent sends a task to another via the A2A protocol, Cerbos evaluates policies to determine whether the requesting agent (on behalf of a user) is authorized to invoke that remote agent's capabilities. Each inter-agent interaction is individually authorized.
How is this different from the MCP integration?
MCP governs tool access within a single agent's context. A2A governs communication between agents. Cerbos can enforce both — controlling what tools an agent can use (MCP) and which other agents it can delegate to (A2A).
Can I control which agents communicate with each other?
Yes. Cerbos policies can restrict agent-to-agent communication based on the requesting user's identity, the source agent, the target agent, and the type of task being delegated. Policies are written in YAML and managed outside your application code.
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Cerbos + Agent2Agent Protocol
- Cerbos policies govern AI agent tool access and data visibility
- Full audit trail for every AI tool call and data access
- Per-user permissions enforced across autonomous agent workflows
- Sub-millisecond policy evaluation with no agent pipeline overhead
Authorization for AI systems
By industry
By business requirement
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What is Cerbos?
Cerbos is an end-to-end enterprise authorization software for Zero Trust environments and AI-powered systems. It enforces fine-grained, contextual, and continuous authorization across apps, APIs, AI agents, MCP servers, services, and workloads.
Cerbos consists of an open-source Policy Decision Point, Enforcement Point integrations, and a centrally managed Policy Administration Plane (Cerbos Hub) that coordinates unified policy-based authorization across your architecture. Enforce least privilege & maintain full visibility into access decisions with Cerbos authorization.