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How to Use the Gumlet MCP in Mastra AI

Build resilient media workflows in Mastra AI. Automate your Gumlet operations with conditional logic and built-in retries.

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Works with every AI agent you already use

…and any MCP-compatible client

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Mastra AI

Connect Gumlet MCP to Mastra AI

Create your Vinkius account to connect Gumlet 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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Conditional media processing workflows

Set up complex logic chains that trigger `create_video_upload` only after verifying your storage state with `list_video_collections`. If an upload fails, your Mastra agent handles the retry logic automatically. This ensures your video pipeline doesn't break during high-traffic periods. You define the success criteria and let the agent manage the steps.

Automated CDN and asset lifecycle

Clean up your library by using `delete_video` based on age or analytics triggers. You can chain this with `get_video_analytics` to automatically remove underperforming assets. Your agent monitors the state of your account and executes these removals on schedule. It keeps your CDN storage lean without manual intervention.

Team and account status monitoring

Keep your organization in the loop by using `list_org_users` to audit access. Your Mastra AI agent can verify account status via `get_account_info` and notify your team if quotas are near capacity. This provides a layer of oversight that keeps your infrastructure stable. You get alerted before issues become critical.

Setup guide

Set up Gumlet 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. 1

    Install dependencies

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

  2. 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. 3

    Discover and inject tools

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

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

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

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

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

Why Choose Vinkius

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Real-time monitoring

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Gumlet MCP in Mastra AI

You instantiate the client and map the tools into your agent definition. Mastra then handles the execution context and tool approval flow.
Absolutely, just call `update_video_thumbnail` within your workflow. You can set this to run automatically after a video finishes processing.
We enforce strict isolation for your credentials. Only your specific agent endpoint can access your Gumlet tools, and all traffic remains encrypted.
You configure retry policies in your agent definition. If a tool call fails, the framework automatically handles the backoff logic.
It touches your video asset metadata and account configuration. We secure this access via a single-use token provided by your Vinkius dashboard.

Start using the Gumlet MCP today

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