Compatible with every major AI agent and IDE
What is the 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.
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.
How it works
- Subscribe to this server
- Enter your OpenFGA API URL and API Token (if applicable)
- Start managing your authorization logic from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Security Engineers — Audit relationship tuples and verify authorization models without manual API calls.
- Backend Developers — Quickly test and iterate on authorization models during development directly from the IDE.
- DevOps & SREs — Monitor store health and manage authorization environments across different clusters.
Built-in capabilities (16)
Perform multiple checks in one request
Check if a user has a relation to an object
Create a new OpenFGA store
Delete an OpenFGA store
Expand a relation into a tree
Get a specific authorization model
Get OpenFGA store details
Check OpenFGA server health
List authorization models
List all objects a user can access
List all OpenFGA stores
List all users who have a relation to an object
Read changes to relationship tuples
Query stored relationship tuples
Write a new authorization model
Add or delete relationship tuples
Why CrewAI?
When paired with CrewAI, OpenFGA (Fine-Grained Auth) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call OpenFGA (Fine-Grained Auth) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
- —
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
OpenFGA (Fine-Grained Auth) in CrewAI
OpenFGA (Fine-Grained Auth) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect OpenFGA (Fine-Grained Auth) to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for OpenFGA (Fine-Grained Auth) in CrewAI
The OpenFGA (Fine-Grained Auth) 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. All 16 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
OpenFGA (Fine-Grained Auth) for CrewAI
Every tool call from CrewAI to the OpenFGA (Fine-Grained Auth) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
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.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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