How to Use the Luma MCP in Mastra AI

Q: Where does Mastra AI store Luma event metadata?

It does not store it. Event metadata fetched via listevents is processed in-memory during agent execution and discarded immediately after the workflow step completes.

Automate complex multi-step Luma event workflows with Mastra AI agents and built-in failure recovery.

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Connect Luma MCP to Mastra AI

Create your Vinkius account to connect Luma 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 Luma with Mastra AI

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Automated guest registration retries

The `add_guests_to_event` tool registers attendees automatically, but network blips can ruin automated workflows. Mastra AI handles these failures by wrapping this MCP Server tool in a workflow engine that automatically retries failed invitations with exponential backoff. If an invite fails, the agent doesn't just crash. It pauses, retries, and only escalates to a human operator if the Luma API remains unreachable after three attempts.

Conditional organization event audits

The `list_organization_events` tool pulls your entire event history, which Mastra AI agents analyze to spot scheduling conflicts. You can set up conditional branches that flag overlapping events and pause for approval before executing any changes. This keeps your calendar clean without giving the agent raw power. It queries the organization's schedule, spots the conflict, and waits for a thumbs-up in Slack before proceeding.

Deploying Luma workflows with Mastra AI

The `create_event` tool lets your agent spin up fresh landing pages, which you can deploy instantly using Mastra AI's one-command setup. This MCP Server connection allows you to build autonomous event-creation pipelines that run on any cloud provider. You write the workflow once, link it to your calendar feeds, and let the agent handle scheduling. The agent coordinates the setup, and the workflow engine manages the cloud execution.

Setup guide

Set up Luma 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 Luma 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: "luma-mcp-client",
  servers: {
    "luma-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Luma MCP in Mastra AI

Mastra AI uses built-in backoff policies when executing tools like `create_event` through this MCP Server. If you hit Luma limits, the agent automatically queues the requests and retries.

Yes. You configure requireToolApproval on the agent for the `add_guests_to_event` tool. The agent halts and waits for human confirmation before sending the invite.

You define the agent with the Luma tools, then use Mastra's deployment command to push it to your cloud. It packages the MCP Server connection details automatically.

Yes. You can register multiple instances of the server, allowing your agent to run `list_organization_events` across different accounts in a single workflow.

It does not store it. Event metadata fetched via `list_events` is processed in-memory during agent execution and discarded immediately after the workflow step completes.

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