How to Use the Skylink MCP in Mastra AI

Q: Can I build complex branching logic using Skylink and mastra-ai?

Yes. If a tool call like getcall returns negative analytics, your flow can automatically branch to run remediation steps instead of proceeding normally.

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…and any MCP-compatible client

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Connect Skylink MCP to Mastra AI

Create your Vinkius account to connect Skylink to Mastra AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Skylink with Mastra AI

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Automated Lead Prioritization

You can build a workflow that triggers the `get_lead` tool and then runs complex logic. If the lead status is 'stalled,' your agent automatically calls `create_task` to assign follow-up steps. This process handles failure gracefully; if creating the task fails, the workflow retries with different parameters before notifying an admin.

Multi-Step Deal Management

Use a sequence of calls starting with `get_account` to gather all necessary details. The workflow then uses this data to run `update_deal`, moving the deal stage only if specific criteria are met. It manages the dependency: the next step won't execute until the previous tool call confirms success, making your automation reliable.

Systematic Contact Creation

Need to onboard a new client? Start with `create_contact` and let the workflow manage all follow-up steps. It can automatically create necessary associated records like tasks or initial leads. This ensures that even if one step fails—say, creating the task—the entire process doesn't just stop; it alerts you to fix the issue.

Setup guide

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

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

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

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Common questions about Skylink MCP in Mastra AI

You define a chain of required tool calls within your workflow. For example, calling `get_lead` then passing that ID to `update_deal` sequentially.

The server touches contact records, deal information, and lead status. These are the primary data points your workflow can read from or write to.

Yes. If a tool call like `get_call` returns negative analytics, your flow can automatically branch to run remediation steps instead of proceeding normally.

Absolutely. You configure the workflow engine to retry failed tool calls (like `create_task`) with exponential backoff, which is essential for flaky API integrations.

The server handles contact records. Your workflows must contain logic to check permissions before any update or creation of sensitive PII occurs.

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