How to Use the Videco MCP in Mastra AI

Q: How do I manage Videco campaigns with Mastra AI?

You set up a multi-step process that calls listcampaigns first. If the initial list call fails, your agent will automatically retry until it gets a successful response.

Q: Can I use Videco to get video analytics with Mastra AI?

Yes, you can include getvideoanalytics in a workflow. The agent will execute this call and wait for the metrics before proceeding, ensuring data integrity across steps.

Q: Does Videco support complex multi-step workflows with Mastra AI?

It does. You can chain tools like getlead followed by createcampaign, and if the campaign creation fails, your workflow engine handles the failure gracefully.

Q: If my Videco process needs to handle data privacy with Mastra AI, what data types are involved?

This server touches Lead details. You'll need to incorporate logic into your workflows that specifically validates and handles the sensitive nature of this lead information before any action is taken.

Build reliable, multi-step video marketing workflows with Mastra AI.

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Connect Videco MCP to Mastra AI

Create your Vinkius account to connect Videco 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 Videco with Mastra AI

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Automate Video Creation Workflows

The `create_video` tool handles the entire personalized video generation process. With Mastra AI, you can build a workflow that calls this function and automatically retries if the API call fails. If one step drops, your agent doesn't crash; it uses its built-in failure handling to try again or notify an administrator.

Manage Leads with Retrying Logic

You can build a workflow that first calls `list_leads` and then processes the data. If fetching the full list fails, Mastra AI automatically retries the call using exponential backoff. This mechanism ensures your critical lead data is retrieved even if the external service hits temporary issues.

Track Campaign Status Reliably

Use `get_campaign` within a complex workflow. If you need to verify campaign details, this tool works reliably inside Mastra AI's engine. The agent will execute the check and wait for confirmation before proceeding to the next step in your defined sequence.

Setup guide

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

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

const result = await agent.generate(
  "List recent Videco 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 Videco. 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 Videco MCP in Mastra AI

You set up a multi-step process that calls `list_campaigns` first. If the initial list call fails, your agent will automatically retry until it gets a successful response.

The server provides various marketing data types, including `Lead details`. You can build workflows that process and act on this structured information after retrieval. It's perfect for complex business logic.

Yes, you can include `get_video_analytics` in a workflow. The agent will execute this call and wait for the metrics before proceeding, ensuring data integrity across steps.

It does. You can chain tools like `get_lead` followed by `create_campaign`, and if the campaign creation fails, your workflow engine handles the failure gracefully.

This server touches `Lead details`. You'll need to incorporate logic into your workflows that specifically validates and handles the sensitive nature of this lead information before any action is taken.

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