How to Use the meetergo MCP in Mastra AI

Q: Can I use meetergo for complex routing in Mastra AI?

You can. By combining getmeetingtype and listusers, you build complex logic that routes leads based on specific criteria.

Build resilient Mastra AI workflows that route leads and manage bookings with automated retry logic.

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Connect meetergo MCP to Mastra AI

Create your Vinkius account to connect meetergo 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 meetergo with Mastra AI

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Claude

Perplexity

Conditional lead routing in Mastra AI

Branch your agent logic based on real-time availability. Your workflow calls `get_user` to verify rep status and then `list_availability` to find the right slot. If the first rep is busy, the agent retries with a different user automatically. It handles the complexity of round-robin routing without custom glue code.

Safe human-in-the-loop booking

Use Mastra AI's tool approval requirement for sensitive operations. The agent proposes a `create_booking` action, but you hold the final say before it writes to the calendar. This adds a layer of safety for high-value enterprise accounts. You keep control while the agent does the research.

Automated booking management

Monitor and manage your calendar lifecycle within your agents. Use `list_bookings` to scan for conflicts and `cancel_booking` to handle last-minute schedule changes. The workflow engine manages the state transitions. If a call fails, the built-in backoff logic ensures the booking request eventually reaches the server.

Setup guide

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

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

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

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Common questions about meetergo MCP in Mastra AI

You use the MCP client to list tools and spread them into your agent definition. Run your workflow in a test environment to verify that `create_booking` behaves as expected.

Yes. Mastra AI handles the retries when the server returns a transient error. You just configure the policy in your agent workflow settings.

You can. By combining `get_meeting_type` and `list_users`, you build complex logic that routes leads based on specific criteria.

The server processes meeting details and user profiles in isolation. Your data is never logged or shared, and the connection remains scoped to your specific agent instance.

Catch the error in your workflow step. You can define a fallback branch to notify an admin or log the issue for manual review.

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