How to Use the Aporia MCP in Mastra AI

Q: How do I register Aporia tools in Mastra AI?

Instantiate new MCPClient with your server ID and endpoint URL. Call mcpClient.listTools() and spread the returned array directly into your Agent's tool configuration. Mastra auto-detects the transport layer for the Aporia MCP server.

Q: How do I find the right monitor ID to use with Aporia and Mastra AI?

Your agent executes listmonitors during the initialization phase to fetch all active rules for a specific model. You parse that list and pass the correct ID into your subsequent workflow steps.

Build self-healing workflows in Mastra AI using Aporia. Catch model drift and trigger automated retries before bad data breaks your pipeline.

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Connect Aporia MCP to Mastra AI

Create your Vinkius account to connect Aporia 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 Aporia with Mastra AI

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Automated Monitor Escalation

`trigger_monitor` forces an immediate evaluation of a specific model configuration when your Mastra AI workflow detects an anomaly. Instead of waiting for a scheduled check, your agent proactively requests a safety run mid-execution. This changes how you handle failures. If the monitor returns a warning, Mastra's workflow engine uses conditional branching to retry the prompt with stricter parameters or fallback to a simpler model.

Workflow-Native MCP Server Guardrails

`validate_guardrails` acts as a hard gate inside your multi-step processes. You feed the LLM output into the Aporia MCP server, checking for toxicity and off-topic deviations before passing the data to the next node. Bad data dies early. If the validation fails, you configure Mastra to execute an exponential backoff retry or route the flagged message to a human-in-the-loop queue using the `requireToolApproval` flag.

Dynamic Agent Diagnostics

`get_model` and `get_metrics` pull exact performance details for your monitored models straight into the agent's context window. Your system reads its own drift metrics and token counts during the run. You stop guessing why a workflow failed. The agent queries the active monitors via `list_monitors` and logs the exact rule that tripped, giving your engineering team a precise root cause analysis.

Setup guide

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

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

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

Instantiate `new MCPClient` with your server ID and endpoint URL. Call `mcpClient.listTools()` and spread the returned array directly into your Agent's tool configuration. Mastra auto-detects the transport layer for the Aporia MCP server.

That is the primary use case. You set a conditional branch that catches the failed validation boolean and triggers a retry loop. The workflow engine handles the exponential backoff automatically.

Mastra catches the timeout and executes your defined fallback path. You decide whether to bypass the safety check or halt the entire pipeline until the endpoint recovers.

Your agent executes `list_monitors` during the initialization phase to fetch all active rules for a specific model. You parse that list and pass the correct ID into your subsequent workflow steps.

The tools read the raw message strings strictly to evaluate safety boundaries. Aporia processes the text to identify names or credit cards, flags the violation, and discards the buffer. No workflow data persists in the connection layer.

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