How to Use the CatAAS MCP in Mastra AI

Q: How do I set up the CatAAS MCP Server in Mastra AI?

After npm install @mastra/mcp, you create a new MCPClient and pass your Vinkius server URL. Then, you can list the tools and spread them into your agent's toolset to make them available to your workflows.

Build resilient workflows that generate cat content. Mastra AI handles retries and branching when the cats don't cooperate.

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Connect CatAAS MCP to Mastra AI

Create your Vinkius account to connect CatAAS 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 CatAAS with Mastra AI

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Create Reliable Cat Content Pipelines

You're building a service that posts a cat picture every day. With Mastra AI, you define the workflow: first, call `list_tags` to get a theme, then use `get_cat_by_tag` to fetch an image. You don't have to write any retry logic yourself. If the API call to the CatAAS server fails, Mastra’s engine tries again automatically with exponential backoff. You can even build in fallbacks. If `get_cat_by_tag` keeps failing, the workflow can branch to call `get_random_cat` instead. Your bot never misses a post.

Build a Multi-Step Meme Bot

Let's say you want a Slack bot that makes custom memes. A user provides a topic. Your Mastra agent first calls `list_tags` to check if the topic is a valid tag. If it is, the agent uses `get_cat_with_tag_and_text`. If the topic doesn't match a tag, the agent's workflow branches to a different path, using `get_cat_with_text` with a generic cat image. This conditional logic is built into Mastra, letting you create smart bots that handle different inputs without a ton of `if/else` statements.

Process Cat Requests with Your Mastra AI MCP Server

Imagine a system where users request custom cat GIFs. You can use Mastra AI to build a worker that pulls requests from a message queue. For each request, the agent's workflow calls `get_random_gif_cat` and then uses another tool to post the result. This MCP Server provides the core creative function. Mastra's workflow engine ensures that if one tool call fails, it can be retried or skipped without crashing the entire process. It’s for building background jobs that need to be dependable.

Setup guide

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

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

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

You add the CatAAS tools to your agent's configuration. Then you can call tools like `get_cat_by_tag` as steps in your workflow, complete with Mastra's native support for conditional logic and retries.

Yes, that's a core feature of Mastra. The engine automatically retries failed tool calls, making your cat-fetching workflows much more robust than a simple API call.

Build a fully automated social media bot. An agent can find a cat using `get_cat_by_tag`, add text using `get_cat_with_tag_and_text`, and post it, all within a single, resilient Mastra AI workflow.

After `npm install @mastra/mcp`, you create a new `MCPClient` and pass your Vinkius server URL. Then, you can list the tools and spread them into your agent's toolset to make them available to your workflows.

Your text and tags are sent to the CatAAS server to generate the image. The connection is secured and managed by Vinkius. The server runs in a zero-trust environment that doesn't persist your input data after the request is fulfilled.

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