How to Use the Claid AI MCP in Mastra AI

Q: How do I register Claid AI tools within a Mastra AI agent?

Install @mastra/mcp and instantiate the client with your Vinkius endpoint URL. You can then call listTools() and spread them directly into the Mastra agent tools array to grant access to image processing.

Q: Do I need to configure webhooks manually for Claid AI and Mastra AI?

The listclaidwebhooks tool allows your Mastra agent to inspect configured webhooks programmatically. This lets your workflow verify the notification system is active before initiating large batch processing jobs.

Build automated ecommerce image pipelines that auto-retry failed runs using Mastra AI and Claid AI.

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Connect Claid AI MCP to Mastra AI

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Setup Claid AI with Mastra AI

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Automated image workflows via Mastra AI MCP Server

The `enhance_image` tool combines upscale, background removal, and HDR adjustments to correct product photos automatically. Mastra AI runs this tool within its workflow engine, ensuring that if a processing step fails, the system retries with exponential backoff. You can build a multi-step pipeline where the agent runs the tool, checks the output, and immediately updates your inventory database. This removes manual QA from your merchant onboarding queue.

Async task tracking with Mastra AI

The `get_processing_task_details` tool retrieves the status and result of an async image processing task. Mastra AI agents use this tool inside conditional branches to pause execution until the high-res render is ready. Instead of blocking your server thread, the workflow handles the wait state natively. You don't have to worry about polling logic because once the status changes to completed, Mastra triggers the next step in your automation chain.

Catalog organization using Mastra AI

The `list_claid_collections` tool retrieves image collections from your account to organize processed assets. Your Mastra AI agent calls this tool to find the correct target folder before running any background removal tasks. This ensures your structured media library stays clean. The agent validates the collection exists, creates it if missing, and routes the new product shots to the exact directory.

Setup guide

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

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

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

Install `@mastra/mcp` and instantiate the client with your Vinkius endpoint URL. You can then call `listTools()` and spread them directly into the Mastra agent tools array to grant access to image processing.

Yes, Mastra AI supports human-in-the-loop approvals. You can configure the workflow to pause before triggering `remove_image_background`, requiring an admin to approve the edit in your dashboard.

Mastra AI uses its built-in workflow engine to handle retries and backoff. If `upscale_image_resolution` hits a rate limit or quota issue, the workflow automatically retries the operation without failing the entire run.

The `list_claid_webhooks` tool allows your Mastra agent to inspect configured webhooks programmatically. This lets your workflow verify the notification system is active before initiating large batch processing jobs.

The MCP integration only processes the image files, source URLs, and collection metadata required for operations like `remove_image_background`. Your image data is processed in an ephemeral V8 sandbox, ensuring no permanent storage of your media files occurs outside your designated collections.

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