How to Use the Frontegg MCP in Mastra AI

Q: How do I configure Frontegg tools in Mastra AI?

Instantiate a new MCPClient and pass your MCP Server URL in the servers object. Then call the list tools method and spread the results into your agent's tool array. Mastra auto-detects the transport protocol.

Automate B2B tenant onboarding workflows with Mastra AI and handle identity provisioning failures gracefully.

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Connect Frontegg MCP to Mastra AI

Create your Vinkius account to connect Frontegg to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Frontegg with Mastra AI

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Mastra AI workflows for B2B identity

Onboarding a new enterprise customer requires sequential tools like `create_tenant` and `create_user`. You need a workflow that creates the account, assigns the first users, and handles API rate limits. Connecting this MCP Server to Mastra AI gives your agents the exact endpoints required to sequence these steps. If the initial tenant creation succeeds, the workflow branches to provision the admin. If the Frontegg API throws a timeout, Mastra automatically catches it and retries with exponential backoff. Your onboarding pipelines become incredibly resilient.

Audit and sync user permissions

Periodic security reviews require pulling massive amounts of data using `list_tenants` and `list_users`. A Mastra agent can loop through the tenant list and then iterate over the users for each account. It builds a complete map of who has access to what. To get granular, the agent calls `list_permissions` and `list_system_roles`. You can pipe this data into a reporting node in your workflow. If it spots a user with excessive permissions, the agent triggers a conditional branch to alert your security channel.

Programmatic machine token rotation

Managing service accounts is painful when done manually, but you can build a Mastra workflow to fetch active service accounts via `list_m2m_tokens`. Set it to run on a cron schedule to ensure you never miss an expiring credential. The agent checks the expiration dates on those tokens. If it finds one that is about to expire, it can alert the owning team or even trigger a rotation process. You handle the connection simply by passing the server URL into the `MCPClient` configuration.

Setup guide

Set up Frontegg MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Frontegg tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "frontegg-mcp-client",
  servers: {
    "frontegg-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Frontegg Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Frontegg tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Frontegg transactions"
);
console.log(result.text);

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

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Common questions about Frontegg MCP in Mastra AI

Instantiate a new `MCPClient` and pass your MCP Server URL in the servers object. Then call the list tools method and spread the results into your agent's tool array. Mastra auto-detects the transport protocol.

Yes. If a tool call fails due to network issues, the built-in workflow engine catches the error. You can configure automatic retries with exponential backoff directly in your workflow definition.

Set the require tool approval flag to true for the deletion tools in your Mastra configuration. The workflow will pause and wait for an administrator to approve the action before executing the API call.

It supports both SSE and streamable HTTP. Mastra will figure out the right transport method automatically when it connects to the endpoint.

The server reads raw user metadata, tenant configurations, and system roles directly from your identity provider. It runs in an ephemeral V8 Isolate sandbox. No data persists on disk after the workflow step completes.

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