How to Use the Brightcove MCP in Mastra AI

Q: How to connect Brightcove to Mastra AI workflows?

Add the server URL to your agent configuration and use the listTools method. Once registered, your agents can execute any video management task as part of a complex workflow.

Build automated video workflows for Mastra AI using the Brightcove MCP Server.

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Connect Brightcove MCP to Mastra AI

Create your Vinkius account to connect Brightcove 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 Brightcove with Mastra AI

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Automate Brightcove tasks in Mastra AI

Chain your video management steps together using the workflow engine. If `delete_video` fails, you can set up a retry loop to handle the error automatically. This keeps your operations running without manual oversight. You define the logic, and the agent executes the sequence.

Conditional video logic with Mastra AI

Use the `list_videos` output to trigger branch conditions in your agent. If a video exceeds a certain duration, you can move it to a specific folder. It removes the need for human intervention. Your agent decides the next step based on the data it pulls from the server.

Reliable Brightcove operations

Leverage exponential backoff for every tool call like `update_video`. It ensures your updates succeed even during periods of high API traffic. Your agents handle the connection stability. You just focus on defining the steps that move your video library assets.

Setup guide

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

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

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

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Common questions about Brightcove MCP in Mastra AI

Add the server URL to your agent configuration and use the `listTools` method. Once registered, your agents can execute any video management task as part of a complex workflow.

The framework supports built-in retries and conditional branching. You can configure the agent to retry `get_video` if the initial request encounters a network hiccup.

Yes, you can enable tool approval for sensitive actions. This ensures a human signs off before the agent executes a command like `delete_video`.

All communications are encrypted and isolated. Only the specific video metadata you request is processed, with no long-term storage of your account secrets.

The server operates in an ephemeral sandbox. Your video titles and folder structures are processed in memory and wiped once the agent task finishes.

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