How to Use the Cloudify MCP in Mastra AI

Q: How do I register the Cloudify MCP Server in Mastra AI?

Install @mastra/mcp and instantiate the client with your Vinkius server URL. Spread mcpClient.listTools() into your Mastra agent's tool array to grant it full infrastructure access.

Q: Can Mastra AI automatically fix a failed Cloudify deployment?

Yes, by combining listexecutions and getdeployment inside a Mastra workflow. The agent detects the failure state, runs diagnostic tools, and triggers recovery steps based on your branching logic.

Q: How does Mastra AI handle human-in-the-loop for Cloudify?

You can set requireToolApproval on sensitive tools like getblueprint or deployment inspection tools. This pauses the Mastra workflow and waits for a manual sign-off before modifying your cloud.

Build resilient, self-healing cloud workflows by combining Mastra AI agents with your Cloudify infrastructure.

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Connect Cloudify MCP to Mastra AI

Create your Vinkius account to connect Cloudify 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 Cloudify with Mastra AI

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Build self-healing workflows with Mastra AI

The `list_executions` tool gives your Mastra agents the exact active workflow bounds to track running deployments. If an execution fails, Mastra's built-in workflow engine catches the error, triggers an exponential backoff, and retries the step automatically. By combining this with conditional branching, your agent checks `list_deployments` after a failure. If the topology is corrupted, the workflow branches to run a clean setup, keeping your infrastructure aligned with your desired state.

Map runtime nodes to automated retries

The `list_nodes` tool identifies specific instances routing your deployment rules so Mastra can inspect individual server states. When a node goes offline, the agent pulls the exact literal limits to determine which VM needs a reboot. Your Mastra client handles this through structured steps, checking `get_deployment` to check the node's structural parent before taking action. You write the logic once in TypeScript, and the agent executes the recovery loops autonomously.

Validate deployment limits before executing

The `list_plugins` tool extracts native deployment capabilities to check your environment supports the required blueprint. Your Mastra AI agent runs this check as a pre-flight step in your MCP pipeline. If the plugin check passes, the agent calls `get_blueprint` to extract the properties driving the active schema. This prevents broken deployments from starting, saving your team from cleaning up half-baked cloud resources.

Setup guide

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

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

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

Install `@mastra/mcp` and instantiate the client with your Vinkius server URL. Spread `mcpClient.listTools()` into your Mastra agent's tool array to grant it full infrastructure access.

Yes, by combining `list_executions` and `get_deployment` inside a Mastra workflow. The agent detects the failure state, runs diagnostic tools, and triggers recovery steps based on your branching logic.

You can set `requireToolApproval` on sensitive tools like `get_blueprint` or deployment inspection tools. This pauses the Mastra workflow and waits for a manual sign-off before modifying your cloud.

Yes, Mastra auto-detects the SSE transport exposed by Vinkius. Your MCP agents maintain a stable connection to query node states and execution limits without polling.

Your raw blueprint schemas and node properties are processed locally within your Mastra runtime. Vinkius hosts the MCP Server in a zero-trust sandbox, ensuring your structural cloud configurations remain private.

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