OpenFGA (Fine-Grained Auth) MCP Server for Pydantic AIGive Pydantic AI instant access to 16 tools to Batch Check Relations, Check Relation, Create Store, and more

Name: OpenFGA (Fine-Grained Auth)
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect OpenFGA (Fine-Grained Auth) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The OpenFGA (Fine-Grained Auth) MCP Server for Pydantic AI is a standout in the Developer Tools category — giving your AI agent 16 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to OpenFGA (Fine-Grained Auth) "
            "(16 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in OpenFGA (Fine-Grained Auth)?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About OpenFGA (Fine-Grained Auth) MCP Server

Connect your OpenFGA instance to any AI agent to manage Relationship-Based Access Control (ReBAC) through natural conversation. OpenFGA is an open-source fine-grained authorization solution inspired by Google's Zanzibar.

Pydantic AI validates every OpenFGA (Fine-Grained Auth) tool response against typed schemas, catching data inconsistencies at build time. Connect 16 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Store Management — Create, list, and delete isolated stores to manage authorization data for different environments or applications.
Authorization Modeling — Define and retrieve complex authorization models using types and relations to represent your system's permissions.
Tuple Management — Write, read, and track changes to relationship tuples that define which users have which relations to specific objects.
Relationship Checks — Instantly evaluate whether a user has a specific relation to an object (e.g., 'can user:anne view document:1?').
Health Monitoring — Quickly check the status of your OpenFGA instance to ensure high availability.

The OpenFGA (Fine-Grained Auth) MCP Server exposes 16 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 16 OpenFGA (Fine-Grained Auth) tools available for Pydantic AI

When Pydantic AI connects to OpenFGA (Fine-Grained Auth) through Vinkius, your AI agent gets direct access to every tool listed below — spanning authorization, rebac, access-control, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

batch

Batch check relations on OpenFGA (Fine-Grained Auth)

Perform multiple checks in one request

check

Check relation on OpenFGA (Fine-Grained Auth)

Check if a user has a relation to an object

create

Create store on OpenFGA (Fine-Grained Auth)

Create a new OpenFGA store

delete

Delete store on OpenFGA (Fine-Grained Auth)

Delete an OpenFGA store

expand

Expand relation on OpenFGA (Fine-Grained Auth)

Expand a relation into a tree

get

Get authorization model on OpenFGA (Fine-Grained Auth)

Get a specific authorization model

get

Get store on OpenFGA (Fine-Grained Auth)

Get OpenFGA store details

health

Health check on OpenFGA (Fine-Grained Auth)

Check OpenFGA server health

list

List authorization models on OpenFGA (Fine-Grained Auth)

List authorization models

list

List objects on OpenFGA (Fine-Grained Auth)

List all objects a user can access

list

List stores on OpenFGA (Fine-Grained Auth)

List all OpenFGA stores

list

List users on OpenFGA (Fine-Grained Auth)

List all users who have a relation to an object

read

Read changes on OpenFGA (Fine-Grained Auth)

Read changes to relationship tuples

read

Read tuples on OpenFGA (Fine-Grained Auth)

Query stored relationship tuples

write

Write authorization model on OpenFGA (Fine-Grained Auth)

Write a new authorization model

write

Write tuples on OpenFGA (Fine-Grained Auth)

Add or delete relationship tuples

Connect OpenFGA (Fine-Grained Auth) to Pydantic AI via MCP

Follow these steps to wire OpenFGA (Fine-Grained Auth) into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 16 tools from OpenFGA (Fine-Grained Auth) with type-safe schemas

Why Use Pydantic AI with the OpenFGA (Fine-Grained Auth) MCP Server

Pydantic AI provides unique advantages when paired with OpenFGA (Fine-Grained Auth) through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your OpenFGA (Fine-Grained Auth) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your OpenFGA (Fine-Grained Auth) connection logic from agent behavior for testable, maintainable code

OpenFGA (Fine-Grained Auth) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the OpenFGA (Fine-Grained Auth) MCP Server delivers measurable value.

Type-safe data pipelines: query OpenFGA (Fine-Grained Auth) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple OpenFGA (Fine-Grained Auth) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query OpenFGA (Fine-Grained Auth) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock OpenFGA (Fine-Grained Auth) responses and write comprehensive agent tests

Example Prompts for OpenFGA (Fine-Grained Auth) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with OpenFGA (Fine-Grained Auth) immediately.

"List all my OpenFGA stores."

"Check if user 'anne' has the 'viewer' relation to 'document:doc1' in store 01H1..."

"Create a new OpenFGA store named 'Security-Audit-Logs'."

Troubleshooting OpenFGA (Fine-Grained Auth) MCP Server with Pydantic AI

Common issues when connecting OpenFGA (Fine-Grained Auth) to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

OpenFGA (Fine-Grained Auth) + Pydantic AI FAQ

Common questions about integrating OpenFGA (Fine-Grained Auth) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your OpenFGA (Fine-Grained Auth) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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