How to Use the Canto MCP in Mastra AI

Q: Is Canto metadata extraction supported in Mastra AI?

Absolutely. Use getimagemetadata to pull properties into your workflow. You can then route those properties to other agents for analysis.

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Connect Canto MCP to Mastra AI

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Setup Canto with Mastra AI

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Automate Canto folder provisioning in Mastra AI

Use `create_canto_folder` inside your Mastra AI agent workflows to build new resource boundaries automatically. You can chain these steps with conditional branching if a folder fails to generate. The server handles the JSON payloads for every new container. Your agents just pass the parameters and wait for the confirmation.

Execute deep Canto asset searches with Mastra AI

Deploy `global_asset_search` as a specialized agent tool to filter through large libraries. Mastra AI handles the retries if the network hits a snag. Your agents find specific images by querying internal arrays directly. It turns your creative library into a searchable database for your autonomous processes.

Control Canto album assignments through Mastra AI

Run `assign_asset_album` to move files across your linking trees. You can set up complex logic to sort assets based on metadata extraction. This keeps your library organized without manual intervention. Each tool call ensures the correct assets land in the right collections.

Setup guide

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

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

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

Mastra AI uses built-in exponential backoff to retry failed calls to the Canto tools. You define the retry logic in your workflow configuration.

Yes. Simply spread the tools into your agent definition. You can mix these with other functions to create complex, automated asset management pipelines.

Absolutely. Use `get_image_metadata` to pull properties into your workflow. You can then route those properties to other agents for analysis.

You can enable approval requirements for any tool. This forces the agent to pause before modifying your albums or deleting assets.

All communication happens through encrypted transport. We only handle the specific image metadata and folder paths you authorize.

Use it with your favorite AI tools

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