OpenFGA (Fine-Grained Auth) MCP. Manage access rules by simply asking your agent.

Q: How does the OpenFGA (Fine-Grained Auth) MCP work with different environments?

You use liststores to see all your available stores. You then use createstore or reference an existing store ID when checking a relation, ensuring you're always testing against the correct data environment.

Q: What if I need to check permissions for many users at once using OpenFGA (Fine-Grained Auth)?

Use the batchcheckrelations tool. This lets you group multiple user and object pairs into one request, making your auditing process much faster than checking them individually.

Q: Can I model a completely new type of permission in OpenFGA (Fine-Grained Auth)?

Yes. You use the MCP to writeauthorizationmodel and define your custom types and relations, which makes the rule available for future checks.

Q: Where do I find out what kind of access a specific user has?

You can run listobjects. This tool gathers all the objects that a user is entitled to access based on their current relationship tuples in the store.

Q: Is OpenFGA (Fine-Grained Auth) MCP suitable for auditing past changes?

Yes. The readchanges tool allows you to query historical records, so you can track when and how a user's permissions were changed over time.

Q: How can I check if a specific user has access to a resource?

You can use the checkrelation tool. Provide the store ID and the relationship details (user, relation, and object) to get an immediate boolean response on whether the access is permitted.

Q: Can I see the history of changes made to relationship tuples?

Yes, the readchanges tool allows you to retrieve the changelog of relationship tuples for a specific store, optionally filtered by object type.

Q: How do I define a new authorization model?

Use the writeauthorizationmodel tool. You will need to provide the store ID, the schema version, and a JSON array of type definitions that describe your relations.

OpenFGA (Fine-Grained Auth) connects your AI agent to an open-source system for Relationship-Based Access Control (ReBAC). Manage complex permissions, define access models, and check user rights against specific resources using natural conversation. It lets you program security policies without writing boilerplate API code.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Give Claude and any AI agent real-world access

Check user permissions

Instantly verifies if a specified user has a defined relationship to a particular object.

Manage data environments

Create, list, and delete isolated stores to keep authorization data separate for different applications or testing phases.

Model system rules

Define and retrieve the complex types and relations that govern how your entire system's permissions work.

Read access history

Queries stored relationship tuples to see exactly which users have what rights to which objects.

Audit object visibility

Lists all the resources (objects) a particular user is allowed to interact with.

Ask an AI about this

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AI Agent

What AI agents can do with OpenFGA (Fine-Grained Auth) MCP: 16 Tools

These tools let you interact with every aspect of OpenFGA authorization, from checking a single user's access to managing entire data stores.

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 OpenFGA (Fine-Grained Auth) MCP

Check Relation

Determines if an individual user has the right to access a specific object.

Create Store

Sets up a brand new, isolated OpenFGA data store for your application.

Delete Store

Permanently removes an existing OpenFGA data store.

Expand Relation

Visualizes a complex permission by expanding it into a readable tree structure.

Get Authorization Model

Retrieves the definition of a specific authorization model type used in your system.

Get Store

Fetches detailed information about an existing OpenFGA store.

Health Check

Quickly verifies the operational status of your entire OpenFGA instance.

List Authorization Models

Presents a list of all authorization models currently defined in your system.

List Objects

Retrieves a comprehensive list of every object that a user has access to.

List Stores

Lists all the different OpenFGA stores you have running.

List Users

Finds and lists every user who has been granted a relationship to an object.

Read Changes

Reads records of changes made to the system's permission tuples over time.

Read Tuples

Queries and retrieves stored relationship data directly from the database.

Write Authorization Model

Writes or updates an authorization model definition in your system.

Write Tuples

Adds new relationship tuples or removes existing ones to manage permissions.

Batch Check Relations

Performs multiple user permission checks in a single request.

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.

OpenFGA (Fine-Grained Auth) MCP is compatible with Claude

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 OpenFGA (Fine-Grained Auth) integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "openfga-fine-grained-auth": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the OpenFGA (Fine-Grained Auth) tools with full Vinkius guardrails applied.

OpenFGA (Fine-Grained Auth) MCP is compatible with VS Code

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"openfga-fine-grained-auth": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

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 each call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with OpenFGA (Fine-Grained Auth), then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,200+ others, all in one place
Add new capabilities to your AI anytime you want
Connections are secured and governed automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog weekly

OpenFGA (Fine-Grained Auth) MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by OpenFGA. 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 CLOUD

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

The Manual Headache of Managing Access Rights

Right now, checking permissions means jumping between dashboards and API playgrounds. You write the query in one place, copy the results to another, manually verify if the data structure is correct, and then paste it into a third tool just to confirm the access status. It’s slow, and you're always worried about missing a single comma or forgetting which environment you're running against.

With this MCP, that manual process evaporates. You simply tell your agent what needs checking—for instance, 'Does the finance team have write access to Q3 reports?' Your agent uses its connection to OpenFGA and runs all the necessary checks (like `check_relation` or `list_objects`) in one go. The result is a clean, immediate confirmation right inside your chat window.

OpenFGA (Fine-Grained Auth) MCP: Defining Access Rules

The biggest manual step that goes away is the need to constantly write and test raw authorization queries. You don't have to remember the exact syntax for expanding a relation or how to structure a batch check; you just ask your agent to perform the action.

This MCP gives you conversational control over security logic. It means you can update, audit, and validate complex permission rules instantly, making security policy management faster and far less risky.

Support 24/7 support@vinkius.com ↗

Security Vinkius Trust Center ↗

SLA Service Level Agreement ↗

Report Listing Send Report ↗

authorization

rebac

access-control

permissions

security-policy

identity-management

What OpenFGA (Fine-Grained Auth) MCP does for your AI

You can use this MCP to manage your application's most sensitive logic: who sees what. Instead of manually constructing authorization queries or clicking through multiple administrative dashboards, you talk to your AI agent and it handles the complexity for you. You define entire data stores, model relationships between users and objects, and track all permissions using plain conversation.

For example, instead of writing a complex SQL join to check if 'User A' can view 'Document B' because they are part of 'Group C', you simply ask your agent to run the authorization check. The MCP handles reading those relationship tuples and instantly evaluating the result. By connecting this OpenFGA instance through Vinkius, you give your AI client direct, conversational control over your security layer.

You can audit models, list all users with specific access rights, or even monitor the health of your entire authorization setup—all without leaving your chat interface.

Built · Hosted · Managed by Vinkius OpenFGA (Fine-Grained Auth) MCP - Manage Permissions

Server ID 019e38ce-7d20-71c6-b082-ce7b67e6b6f4

Vinkius Inspector

Compliance Grade A+

Score 98.33/100

Report View Report ↗

Benefits of connecting OpenFGA (Fine-Grained Auth) MCP

You eliminate manual API calls. Instead of writing code to check if a user has permission, you tell your agent to run check_relation, and it handles the complex logic immediately.

It keeps your data clean. You can use list_stores to keep sensitive environments (like 'Production' vs. 'Staging') completely isolated within separate stores.

You gain full visibility into permissions. Running read_tuples lets you query stored relationship data, so you always know exactly who has access to what.

Development gets faster. Developers use the MCP to write_authorization_model and instantly test changes without deploying new code just for a policy tweak.

You get immediate health checks. The health_check tool lets SREs quickly verify system availability, minimizing downtime due to authorization issues.

OpenFGA (Fine-Grained Auth) MCP use cases

01 01

Auditing access after a security incident

An engineer needs to know if three different users can view a specific sensitive document. Instead of running three separate manual checks, they prompt their agent: 'List all users who have the viewer relation to document:123.' The agent executes list_users and provides an instant list.

02 02

Implementing a new feature with complex rights

A backend developer needs to add a new type of permission. They use the MCP to run get_authorization_model to see existing patterns, then use write_authorization_model to define and test the new rules before committing any code.

03 03

Preparing for multi-environment deployment

A DevOps team needs to ensure that their staging environment is completely separate from production. They use the agent to create_store specifically named 'Staging' and another called 'Production', ensuring no data overlap.

04 04

Reviewing historical permission changes

A security manager wants to see if an admin accidentally granted access last week. They ask the agent to read_changes on a specific object, immediately retrieving a timeline of every relationship tuple modification.

OpenFGA (Fine-Grained Auth) MCP tradeoffs

What to watch out for, and the recommended way to handle each one.

Writing authorization logic in application code

Avoid

If you embed permission checks (like checking if user X is in group Y) into your main Python files, those rules are hard to update and require a full redeployment just for one policy change.

Instead

Use this MCP to define the rule set using write_authorization_model. This keeps the logic separate from the application code. When a policy changes, you only update the model via your agent, not your codebase.

Checking permissions in isolation

Avoid

Calling simple API endpoints one by one to check access for 10 different users and 20 different resources is tedious, error-prone, and slows down the workflow.

Instead

Use batch_check_relations. This tool lets you pass multiple user/object pairs in a single request, getting all the answers back efficiently.

Assuming data integrity

Avoid

Relying on manual database queries to verify relationship tuples without proper tracking leads to outdated or inaccurate security records.

Instead

Use read_tuples and read_changes. These tools give you a verified, auditable view of the current state and all historical changes to your access records.

When to use OpenFGA (Fine-Grained Auth) MCP

Use this MCP if your core problem is defining and enforcing 'who can do what' based on their relationship to an object. If your security model is complex, relying on groups and types (ReBAC), this tool is essential. Think of it as the central brain for all permissions.

However, don't use this MCP if you simply need to read or write basic unstructured data (like a user profile name or a transaction amount). For those tasks, standard database connectors are better suited. You also shouldn't rely on it for general logging; use dedicated monitoring tools for that. If your only goal is listing all users, the list_users tool helps, but if you need to act on that user list (e.g., send them an email), you need a separate messaging or workflow MCP instead.

Frequently asked questions about OpenFGA (Fine-Grained Auth) MCP

How does the OpenFGA (Fine-Grained Auth) MCP work with different environments? +

You use list_stores to see all your available stores. You then use create_store or reference an existing store ID when checking a relation, ensuring you're always testing against the correct data environment.

What if I need to check permissions for many users at once using OpenFGA (Fine-Grained Auth)? +

Use the batch_check_relations tool. This lets you group multiple user and object pairs into one request, making your auditing process much faster than checking them individually.

Can I model a completely new type of permission in OpenFGA (Fine-Grained Auth)? +

Yes. You use the MCP to write_authorization_model and define your custom types and relations, which makes the rule available for future checks.

Where do I find out what kind of access a specific user has? +

You can run list_objects. This tool gathers all the objects that a user is entitled to access based on their current relationship tuples in the store.

Is OpenFGA (Fine-Grained Auth) MCP suitable for auditing past changes? +

Yes. The read_changes tool allows you to query historical records, so you can track when and how a user's permissions were changed over time.

How can I check if a specific user has access to a resource? +

You can use the check_relation tool. Provide the store ID and the relationship details (user, relation, and object) to get an immediate boolean response on whether the access is permitted.

Can I see the history of changes made to relationship tuples? +

Yes, the read_changes tool allows you to retrieve the changelog of relationship tuples for a specific store, optionally filtered by object type.

How do I define a new authorization model? +

Use the write_authorization_model tool. You will need to provide the store ID, the schema version, and a JSON array of type definitions that describe your relations.

Give Claude and any AI agent real-world access

What AI agents can do with OpenFGA (Fine-Grained Auth) MCP: 16 Tools

Check Relation

Determines if an individual user has the right to access a specific object.

Create Store

Sets up a brand new, isolated OpenFGA data store for your application.

Delete Store

Permanently removes an existing OpenFGA data store.

Expand Relation

Visualizes a complex permission by expanding it into a readable tree structure.

Get Authorization Model

Retrieves the definition of a specific authorization model type used in your system.

Get Store

Fetches detailed information about an existing OpenFGA store.

Health Check

Quickly verifies the operational status of your entire OpenFGA instance.

List Authorization Models

Presents a list of all authorization models currently defined in your system.

List Objects

Retrieves a comprehensive list of every object that a user has access to.

List Stores

Lists all the different OpenFGA stores you have running.

List Users

Finds and lists every user who has been granted a relationship to an object.

Read Changes

Reads records of changes made to the system's permission tuples over time.

Read Tuples

Queries and retrieves stored relationship data directly from the database.

Write Authorization Model

Writes or updates an authorization model definition in your system.

Write Tuples

Adds new relationship tuples or removes existing ones to manage permissions.

Batch Check Relations

Performs multiple user permission checks in a single request.

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

The Manual Headache of Managing Access Rights

OpenFGA (Fine-Grained Auth) MCP: Defining Access Rules

authorization

rebac

access-control

permissions

security-policy

identity-management

What OpenFGA (Fine-Grained Auth) MCP does for your AI

How to set up OpenFGA (Fine-Grained Auth) MCP

Who uses OpenFGA (Fine-Grained Auth) MCP