Authorize LangChain agent tool calls with Cerbos
Control which tools your LangChain agents can invoke with fine-grained, policy-driven authorization powered by Cerbos.
Tool authorization
Control which LangChain tools each user or role can invoke with fine-grained Cerbos policies
Context-aware decisions
Authorize tool calls based on user identity, roles, attributes, and request context at runtime
Audit every tool call
Every authorization decision is logged with full context, giving you a complete audit trail of agent behavior
How Cerbos works with LangChain
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 LangChain, 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 LangChain tool calls
- Define policies for tool access, Write YAML policies that specify which tools each user or role can invoke based on identity, attributes, and context.
- Agent requests authorization before each tool call, Before invoking a tool, the LangChain agent sends the user context, tool name, and target resource to the Cerbos PDP.
- Cerbos evaluates the request against policies, The PDP applies fine-grained rules considering the user's identity, role, and any additional attributes you provide.
- Tool call proceeds or is blocked, Cerbos returns an allow or deny decision. The agent framework enforces it, with every decision logged for audit.
FAQ
How does Cerbos authorize LangChain tool calls?
Before a LangChain agent invokes a tool, it sends the user context, tool name, and target resource to the Cerbos PDP. Cerbos evaluates fine-grained policies and returns an allow or deny decision, ensuring agents only use tools the requesting user is authorized for.
Can I control tool access per user or role?
Yes. Cerbos policies are attribute-based, so you can restrict tool access by role, department, subscription tier, or any other context you provide. Policies are written in YAML and managed outside your application code.
Does this work with LangGraph?
Yes. Cerbos integrates at the tool-call boundary, so it works with both standard LangChain agents and LangGraph workflows. Each tool invocation is individually authorized.
Learn more about Cerbos
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Cerbos + LangChain
- 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
Useful links
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.