ROC AUC Evaluator MCP Server for Mastra AIGive Mastra AI instant access to 1 tools to Calculate Roc Auc
GDPR Free for SubscribersMastra AI is a TypeScript-native agent framework built for modern web stacks. Connect ROC AUC Evaluator through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
Ask AI about this MCP Server for Mastra AI
The ROC AUC Evaluator MCP Server for Mastra AI is a standout in the Developer Tools category — giving your AI agent 1 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"roc-auc-evaluator": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "ROC AUC Evaluator Agent",
instructions:
"You help users interact with ROC AUC Evaluator " +
"using 1 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with ROC AUC Evaluator?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About ROC AUC Evaluator MCP Server
The Area Under the Receiver Operating Characteristic Curve (ROC AUC) is a vital metric for evaluating binary classification models. Because it involves sorting probabilities and integrating the area under a curve iteratively, Large Language Models are mathematically incapable of calculating exact AUC scores from raw arrays. The ROC AUC Evaluator offloads this task to local Node.js processes, instantly returning mathematically rigorous AUC metrics using the exact trapezoidal rule.
Mastra's agent abstraction provides a clean separation between LLM logic and ROC AUC Evaluator tool infrastructure. Connect 1 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
The ROC AUC Evaluator MCP Server exposes 1 tools through the Vinkius. Connect it to Mastra AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 1 ROC AUC Evaluator tools available for Mastra AI
When Mastra AI connects to ROC AUC Evaluator through Vinkius, your AI agent gets direct access to every tool listed below — spanning binary-classification, model-evaluation, mathematical-computation, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Calculate roc auc on ROC AUC Evaluator
Calculates the exact Area Under the ROC Curve (AUC) for binary classification
Connect ROC AUC Evaluator to Mastra AI via MCP
Follow these steps to wire ROC AUC Evaluator into Mastra AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
npm install @mastra/core @mastra/mcp @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Mastra AI with the ROC AUC Evaluator MCP Server
Mastra AI provides unique advantages when paired with ROC AUC Evaluator through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add ROC AUC Evaluator without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every ROC AUC Evaluator tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
ROC AUC Evaluator + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the ROC AUC Evaluator MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query ROC AUC Evaluator, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed ROC AUC Evaluator as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query ROC AUC Evaluator on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using ROC AUC Evaluator tools alongside other MCP servers
Example Prompts for ROC AUC Evaluator in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with ROC AUC Evaluator immediately.
"I have true binary outcomes and the predicted probability scores from my model. Calculate the exact ROC AUC score."
"Here are 50 true labels and 50 probabilities. Can you use the ROC evaluator and tell me if my model performs better than random guessing (AUC > 0.5)?"
"I have probability arrays for Model A and Model B for the same actual test set. Find the AUC for both and tell me which one is superior."
Troubleshooting ROC AUC Evaluator MCP Server with Mastra AI
Common issues when connecting ROC AUC Evaluator to Mastra AI through Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpROC AUC Evaluator + Mastra AI FAQ
Common questions about integrating ROC AUC Evaluator MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
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