Download PDFMarkdown Version
ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Agent Evaluation Metrics Calculator with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Stop guessing. Get hard data on accuracy and efficiency.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 3 capabilities

The complete Agent Evaluation Metrics Calculator capability set.

These are the exact actions your AI can choose when you ask it to work with Agent Evaluation Metrics Calculator.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Agent Evaluation Metrics Calculator.

  1. 01

    Calculate core metrics

    Calculates the foundational performance indicators (accuracy, precision, recall, and F1 score) based on task outcomes

  2. 02

    Calculate efficiency metrics

    Analyzes the operational cost and speed of the agent

  3. 03

    Calculate composite and health

    Generates a single performance score and determines if the agent is underperforming relative to a baseline

Observed, not estimated

803ms average. Fast in production.

Agent Evaluation Metrics Calculator is checked daily against the live service.

Daily averagePeak 978ms
Aug 20Today
Fastest day
645ms
Slowest day
978ms
14-day trend
Slowing+26%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Agent Evaluation Metrics Calculator, so you can see the experience inside your AI.

It does not authenticate your account with Agent Evaluation Metrics Calculator. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Agent Evaluation Metrics Calculator Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_U0L7ecHOaTRSDq7nAgL5eY45DyQTMS1ZlC0QwKTz/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Agent Evaluation Metrics Calculator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "agent-evaluation-metrics-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_U0L7ecHOaTRSDq7nAgL5eY45DyQTMS1ZlC0QwKTz/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Who it's for

Built for the work Agent Evaluation Metrics Calculator owners hand off.

This MCP is built for teams that need to move beyond anecdotal testing. If you build AI agents and need to prove their reliability, cost-effectiveness, and consistency, this capability gives you the objective data to back up your claims.

  • 01

    ML Engineer

    Use this to build automated testing pipelines that track model drift and performance degradation over time.

  • 02

    Data Scientist

    Run deterministic evaluations to compare multiple agent versions against a single, quantifiable benchmark.

  • 03

    AI Product Manager

    Get clear metrics on the trade-offs between agent performance, speed, and API costs before launching a feature.

FAQ

Questions Agent Evaluation Metrics Calculator owners ask.

  • 01

    What kind of data do I need to run this MCP?

    You need structured data about the agent's performance. Specifically, you must provide task outcomes (expected vs. actual), along with operational metrics like average latency and tokens used.

  • 02

    Is this just a dashboard for my agent's scores?

    No, this is a functional MCP. You connect it to your agent, and your AI client runs the calculations for you. It's a deterministic engine, not just a viewing portal.

  • 03

    Does this compare my agent to other models?

    It doesn't compare your agent to other models. It measures your agent's performance against a defined baseline or against its own historical best performance.

  • 04

    What is the difference between the composite score and the core metrics?

    Core metrics (like accuracy) are single indicators. The composite score is a weighted average that combines accuracy, latency, and efficiency into one single number, giving you a holistic health check.

  • 05

    Can I use this for non-AI tasks?

    No. This MCP is specifically designed for evaluating the performance, cost, and reliability of AI agents and models.

Explore

More in Developer Tools

Suggestions