Cerbos MCP. Verify permissions and compliance instantly.
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Cerbos helps you manage complex access policies by connecting your authorization logic directly to your AI workflow. It lets developers test permissions, plan data queries based on user roles, and ensure every action adheres to strict compliance rules without needing manual API calls or complicated internal tooling.
This MCP handles resource evaluation for everything from database reads to application writes.
What your AI agents can do
Authzen evaluation
Checks a single access request using standardized entity models for compliance review.
Authzen evaluations
Performs batch checks on multiple access requests, supporting complex rule semantics like deny-on-first-deny.
Check resources
Reads policies to verify if a specific principal can perform an action on given resources.
You check if a user has permission to perform an action on a defined set of resources.
The system creates query plans that automatically filter results based on the user's allowed permissions.
You run batch checks against multiple requests, respecting granular rules like deny-on-first-deny semantics.
The agent pulls metadata about the current policy engine instance or its required configuration endpoints.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Cerbos: 6 Tools for Policy Management
These tools allow you to audit authorization logic, generate query plans, and verify resource permissions programmatically using your agent.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Cerbos on Vinkius019e3875authzen evaluation
Checks a single access request using standardized entity models for compliance review.
019e3875authzen evaluations
Performs batch checks on multiple access requests, supporting complex rule semantics like deny-on-first-deny.
019e3875check resources
Reads policies to verify if a specific principal can perform an action on given resources.
019e3875get authzen config
Retrieves the necessary endpoint URLs required for running AuthZEN API calls.
019e3875get server info
Returns key build details, including the current version of the policy engine instance.
019e3875plan resources
Generates an Abstract Syntax Tree (AST) query plan for retrieving data a principal is allowed to access.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Cerbos, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cerbos. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 6 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Dealing with authorization means constantly guessing.
Today, verifying access rights feels like a manual detective job. You write code that assumes permission exists, then you have to jump into a separate testing tool or call an API just to check if the user actually has permission for that action. This means copying data from one dashboard and pasting it into another service's test console—a slow loop of 'did I include the right role ID?'
With this MCP, you treat policy validation like any other function call. You simply ask your agent to check the rights needed. The answer comes back instantly: ALLOWED or DENIED, with zero manual context switching required. It keeps the entire process inside your chat interface.
Plan access using `plan_resources`
Before you write a single SELECT statement, you normally have to guess which columns or rows are visible. You might pull everything and then try to filter it in code, risking data leakage or performance hits.
The MCP lets the agent run `plan_resources`. It figures out what your user *should* see based on policies and gives you a query plan that includes all necessary filters built-in. That's secure, efficient querying right there.
What you can do with this MCP connector
Need to know if a user can actually do something before writing the code? This connector lets you talk to your policy engine like it's a natural conversation. You stop guessing about permissions and start validating them instantly.
Instead of building out complex, multi-service authorization middleware, your agent handles it all. It verifies exactly what a principal can access on specific resources or even generates the query plan needed just for that user. This capability is critical when you’re integrating services from multiple domains—you can chain this MCP with others to build automations across platforms.
The platform running this connection, Vinkius, ensures your credentials pass through a zero-trust proxy. Your keys never sit on disk; they only travel in transit. That means whether you're auditing policies or planning resource access, the security layer is always active and auditable.
019e3875-b811-7120-ad7b-d6113ef92763 
How Cerbos MCP Works
- 1 First, connect your AI client to this MCP and provide your Cerbos instance base URL.
- 2 Next, use it in conversation—ask the agent specific policy questions or request a plan for data retrieval.
- 3 You get back a clear, actionable validation result: whether the requested action is allowed or denied by the current policies.
The bottom line is you offload all access control logic to the engine, treating it like another service call in your workflow.
Who Is Cerbos MCP For?
This MCP is essential for Security Auditors and Software Engineers who dread manual API calls. It’s for anyone whose job requires proving that data access rules are followed correctly before a single line of production code runs.
Verifies permission logic across different roles and resource attributes without running manual scripts.
Debugs complex RBAC/ABAC policies by asking the agent to check specific resources right in the chat interface.
Monitors the policy engine's metadata and configuration status, ensuring proper deployment boundaries are met.
What Changes When You Connect
- Stop running manual API calls for simple checks. Use
check_resourcesto verify a principal's access on resources directly through conversation. - Improve data query accuracy by using
plan_resources. The agent generates an AST that filters database results based strictly on user permissions, so you never over-fetch data. -
authzen_evaluationslets you test dozens of complex access requests at once. It supports semantics like deny-on-first-deny for reliable compliance testing. - Debugging policies is faster when the agent handles it. You can run
authzen_evaluationto check specific, single actions against your defined rules. - The system keeps you safe and compliant because Vinkius ensures credentials pass through a zero-trust proxy. Your keys never sit on disk.
Real-World Use Cases
A developer needs to test if a new user profile can delete records.
Instead of deploying code and hoping it works, the engineer asks the agent to run check_resources for 'user:123' on 'profile:xyz' with the action 'delete'. The system confirms (or denies) permission instantly.
A data scientist needs a filtered dataset for a report.
The agent uses plan_resources to generate an AST query plan. This ensures the resulting database query only pulls records where the user's department matches the resource's metadata.
A security team needs to check compliance across multiple roles.
The auditor runs authzen_evaluations against a batch list of 50 different access requests. The tool processes them all, respecting the defined 'permit-on-first-permit' semantics.
An infrastructure team needs to know if the policy engine is updated.
The DevOps agent calls get_server_info and immediately reports the instance version and build details, confirming the current operational status of the system.
The Tradeoffs
Checking permissions one by one.
Manually calling a separate endpoint for every single user/resource pair to see if they are allowed access, which is slow and brittle.
→
Use authzen_evaluations. This tool processes multiple requests in a batch, saving you time and ensuring consistent results across dozens of policy checks.
Writing complex queries without considering user roles.
Building SQL that pulls all records from a table, only to find out later the application breaks because it included restricted data.
→
Run plan_resources first. This generates an AST query plan that automatically incorporates resource ownership and role constraints, making your code secure by design.
Assuming the policy engine is running correctly.
Starting a new development session without confirming the underlying server version or configuration endpoints are correct.
→
Always call get_server_info and then use get_authzen_config. This confirms both the operational status of the instance and the necessary API connection points.
When It Fits, When It Doesn't
Use this MCP if your core problem is 'Can X do Y on Z?'. You need to test, validate, or plan based on access policies. If you're doing development work where resource ownership matters—like filtering a database result set or checking an action before committing code—this tool is necessary. Don't use it if you just need general application state data (use a standard API connector for that). Also, don't rely on get_server_info alone; always pair it with get_authzen_config to make sure the environment is configured correctly before testing policies. This MCP handles the 'authorization layer.'
Common Questions About Cerbos MCP
How does the `check_resources` tool work? +
The check_resources tool evaluates if a specific principal is allowed to perform an action on one or more resources. It's read-only, so you can test policies without modifying any data.
Is `authzen_evaluations` better than `authzen_evaluation`? +
authzen_evaluations is better if you have a list of many requests to check. It handles batch processing and supports advanced rules, which is crucial for large-scale compliance audits.
What should I use first when setting up this MCP? +
Start by calling get_server_info to confirm the instance version. Then run get_authzen_config to make sure your agent has all the required API endpoints before testing policies.
Can I use this MCP for database querying? +
Yes, you can generate query plans using plan_resources. This tool creates an Abstract Syntax Tree (AST) that dictates exactly which data fields your user should be able to see.
How do I confirm the correct endpoints for my policies using `get_authzen_config`? +
It returns all necessary endpoint URLs for the AuthZEN APIs. This prevents connection errors before you run any evaluations. It's perfect for initial setup verification, ensuring your agent connects to the right services.
If I have hundreds of access requests, is `authzen_evaluations` the right tool? +
Yes, this tool handles batch evaluation efficiently. Instead of running individual calls, you submit a list of requests at once. This makes processing large volumes of access policy checks much faster.
What details does `get_server_info` provide if I suspect my Cerbos instance is outdated? +
It gives the precise version and build date of your entire instance. You can use this to audit whether you're running on a stable, up-to-date release or if an upgrade is needed.
Can I check permissions against multiple types of resources using `check_resources`? +
Absolutely. The tool evaluates permissions for any principal across a set of specified resources. You just pass the list, and it checks your policies instantly without needing separate calls.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.