Aserto MCP for AI. Verify any access decision instantly.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
How this MCP server connects to your AI agent
Aserto manages authorization rules by letting your AI client run policy queries against complex access control systems. You can check if a user has permission for an action, inspect deep decision logic, or audit who accessed what resource and when.
It lets you treat fine-grained security policies as simple conversational checks.
What AI agents can do with Aserto Automation
Authz decisiontree
Retrieves a detailed map of values across all policy modules, showing the complete decision logic path.
Authz is
Checks whether a specific user identity has permission to perform an action based on current policies.
Authz query
Allows you to execute custom Rego queries against the main policy authorizer for deep data inspection.
Determine if a specific user is authorized to perform any action based on established security policies.
Run custom, deep queries against the underlying policy logic to inspect system data or test complex rulesets.
Retrieve a full map of the decision tree values to see exactly how the policies processed a request.
Send direct commands to connected edge authorizers, ensuring policy instances sync correctly across your infrastructure.
List and retrieve decision logs, maintaining a clear record of every authorization event that occurred in the system.
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What AI agents can do with Aserto MCP: 7 Tools for Policy Management
Use these specialized tools to check user authorization, execute complex policy logic, and manage the complete lifecycle of your access control decisions.
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 Aserto on VinkiusAuthz Decisiontree
Retrieves a detailed map of values across all policy modules, showing the complete decision logic path.
Authz Is
Checks whether a specific user identity has permission to perform an action based on...
Authz Query
Allows you to execute custom Rego queries against the main policy authorizer for...
Control Plane Exec
Sends commands directly to a connected Edge Authorizer, useful for syncing policies...
Get Decision Log
Gets a signed download URL so you can retrieve an archived decision log object...
List Decision Logs
Lists all available storage objects containing past decisions and audit logs for inspection.
Query Decision Logs
Retrieves the last N authorization decisions from the decision log storage objects.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Claude AI
Open Claude Settings
Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
Add Custom Connector
Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:
https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp
Replace [YOUR_TOKEN_HERE] with your token
from cloud.vinkius.com. For OAuth-protected servers, expand
Advanced settings to add credentials.
Start a conversation
Open a new chat. The Aserto integration is available immediately — no restart needed.
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 Aserto, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
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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
Built on the Model Context Protocol (MCP) for 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 connection provides 7 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Dealing with access control means clicking through half a dozen dashboards., Solved with Vinkius AI Gateway
Today, verifying an access decision is a nightmare. You have to jump between the policy console, the audit logs, and various developer tools. You run one check, find it insufficient, then you manually copy identifiers into another tool to see if that specific resource ID was ever accessed. It's tedious, slow, and easy for human error to creep in.
With this MCP, the process flips entirely. You just ask your agent, 'Was user X authorized?' The system runs the policy engine itself, giving you the definitive answer—all at once. Your AI client handles the complexity; you only deal with the question.
Aserto MCP gives you full visibility into every decision.
You no longer have to rely on guesswork when a feature fails or an audit flags a discrepancy. You can use authz_decisiontree to map the entire policy flow, and then run list_decision_logs to prove exactly what happened historically.
It changes everything. Instead of being limited by manual API calls or complex developer workflows, you get a clear, conversational interface that speaks directly to your security needs.
What your AI can actually do with this
Your agent connects directly to Aserto's rules engine, letting you manage and evaluate complex access control policies using natural conversation. Forget writing boilerplate API calls just to see if someone can read a document; your AI client handles the logic for you. You simply ask, 'Can User X do Y on Resource Z?' The system executes the full policy check instantly.
Need more depth? Run custom queries against the ruleset itself or view the complete decision path taken by the authorizer to understand exactly why a decision was made. It even helps manage policies deployed across different edge locations. This MCP provides comprehensive visibility into your security decisions, all hosted and managed through Vinkius.
You get immediate answers on permissions, audit logs, and policy structure without ever touching an API key or writing Rego code.
019ea5e1-2e5b-713a-826a-73d34035e94a 
Here's how it actually works
The bottom line is: you ask a question about access control in plain language, and this MCP executes the complex security checks instantly.
First, connect your AI client to this MCP by supplying your Aserto Tenant ID, API URL, and required API keys.
Next, you ask a question about access control—for example, 'Can the admin read document 45?'—and your agent invokes the appropriate policy tool.
Finally, the system returns an immediate, actionable decision (true/false) along with detailed logs or query results.
Who is this actually for?
Security engineers need this when they have to verify policy changes quickly without manually calling APIs. Compliance officers use it to generate audit trails that prove regulatory adherence. Backend developers rely on it for integrated, run-time access control testing.
Testing proposed policy changes by running checks and queries before deploying them into production.
Integrating fine-grained access control (FGAC) logic directly into application code for debugging and development testing.
Gathering full decision logs to prove that current policies meet specific regulatory requirements or audit standards.
What Changes When You Connect
You skip manual API calls entirely. Instead of writing code to check permissions, you simply ask your agent, 'Is this user authorized?' and get an immediate true/false answer via authz_is.
Audit trails are instant. Need to prove who accessed what last month? Use list_decision_logs to find the correct log object, then use query_decision_logs to pull the specific records you need for compliance checks.
Debugging complex policies gets easier. When a decision seems wrong, don't guess why. Use authz_decisiontree to map out the exact logic path the system took and pinpoint the flaw.
Manage distributed security with confidence. If you have multiple policy endpoints, use control_plane_exec to send commands that ensure all your edge authorizers are perfectly synced with the central ruleset.
Deep dive into policies without risk. Instead of relying on preset checks, run custom queries using authz_query. This lets you inspect underlying data or test logic not covered by standard tools.
See it in action
Verifying new feature access for a client
A security engineer needs to confirm if a premium user can view certain financial reports. They prompt their agent: 'Check if user X is authorized to read the Quarterly Report.' The system runs authz_is and confirms the decision, saving hours of manual testing against the API.
Investigating a data leak incident
A compliance officer needs to prove that only authorized staff viewed sensitive documents. They use list_decision_logs to find all available logs and then query_decision_logs to pull every decision made for the affected resource ID.
Debugging a complex role hierarchy
A backend developer finds that 'editor' roles sometimes get unexpected read access. They use authz_query to run a specific Rego query against data.system.roles, exposing the exact policy rule causing the unintended permission.
Updating policies across global regions
The infrastructure team updates core rules and needs to ensure all regional endpoints are using them. They use control_plane_exec to send a sync command, guaranteeing consistency across every deployed edge authorizer.
The honest tradeoffs
Trying to debug policies manually
Manually logging into the policy console and clicking through multiple tabs just to find out why a user was denied access.
Instead, ask your agent to use authz_decisiontree. This tool instantly maps out every step of the decision process, telling you exactly which rule failed or passed.
Over-relying on simple permission checks
Only using basic access tools and missing crucial data points because a policy involves complex resource context (e.g., time/department).
Use authz_query to run custom Rego logic against the full set of system variables, ensuring you test every edge case your business requires.
Forgetting historical context
Assuming today's access rules are sufficient without checking if previous policy changes broke logging or audit trails.
Always start by using list_decision_logs to confirm the availability of decision records, then use query_decision_logs for verifiable history.
When It Fits, When It Doesn't
Use this MCP if your primary job involves asking complex questions about 'who can do what' and you need real-time answers based on a formal policy engine. You must have policies written in Rego format that you want to test or audit.
Don't use it if you just need simple user management (like creating accounts) or basic data retrieval (like listing users). For those, look for general CRUD tools. If your requirement is purely about message routing or sending emails, use a dedicated messaging tool instead of wasting time with policy checks. This MCP solves authorization; it doesn't solve task execution.
Questions you might have
How do I check if a user is authorized using Aserto MCP? +
You use the authz_is tool. Simply ask your agent who needs permission and what resource they want to access, and it will return a definitive true or false decision based on your policies.
Can I run custom queries with Aserto MCP? +
Yes, you use the authz_query tool. This allows you to execute specific Rego queries against the underlying policy data for advanced inspection beyond standard checks.
How does Aserto MCP help with compliance auditing? +
You maintain a clear record by using list_decision_logs and query_decision_logs. This gives you an instant, verifiable audit trail of every access event for regulatory reporting.
What if I need to update policies on multiple systems? +
Use the control_plane_exec tool. It sends commands directly to your connected Edge Authorizers, ensuring that policy changes sync consistently across all your deployed locations.
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