How to Use the MonkeyLearn MCP in Mastra AI

Q: How do I see my MonkeyLearn classifiers in Mastra AI?

Use the listclassifiers tool to retrieve a list of your models. Your agent can display these options or select one based on the current context.

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Connect MonkeyLearn MCP to Mastra AI

Create your Vinkius account to connect MonkeyLearn 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 MonkeyLearn with Mastra AI

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Automated classification workflows in Mastra AI

Chain `classify_text` into your agent's logic to route support tickets automatically. If the model is busy, you can set up retries within your workflow engine. The server handles the heavy lifting while Mastra AI manages the state. You can build complex paths that branch based on the tags returned by the classification.

Robust extraction logic for Mastra AI

Use `extract_text` to pull specific entities from customer emails during an automated sequence. This keeps your data clean and ready for downstream processing. You gain full control over the sequence. If an extraction fails, your agent can log the error or trigger a fallback process using the same toolset.

Manage your MonkeyLearn MCP Server pipelines

Query your existing setup with `list_pipelines` and `list_workflows` to keep your agent informed of available resources. It prevents hard-coding IDs into your scripts. Your agents stay in sync with your account activity. When you update a model, the agent detects the change through these listing tools without requiring a deployment restart.

Setup guide

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

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

const result = await agent.generate(
  "List recent MonkeyLearn transactions"
);
console.log(result.text);

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Common questions about MonkeyLearn MCP in Mastra AI

Add the server URL to your agent configuration and spread the tools into your agent instance. This makes every MonkeyLearn tool available for your automated steps.

Yes, you can define retry logic in your Mastra AI workflow. If the MonkeyLearn MCP Server returns an error, the agent can attempt the call again based on your rules.

You can use the requireToolApproval setting to pause the workflow. This lets a human verify the classification before the agent proceeds.

Your text data is processed only when you invoke a tool. We treat all text payloads as sensitive and advise filtering PII before transmission.

Use the `list_classifiers` tool to retrieve a list of your models. Your agent can display these options or select one based on the current context.

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