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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Agent Scoring Engine with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Get stable, reproducible metrics for your autonomous systems.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 4 capabilities

The complete Agent Scoring Engine capability set.

These are the exact actions your AI can choose when you ask it to work with Agent Scoring Engine.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Agent Scoring Engine.

  1. 01

    Adjust weights for correlation

  2. 02

    Calculate agent scores

    0 Calculates normalized composite scores and volatility for a set of agents

  3. 03

    Identify pareto frontier

  4. 04

    Rank agents

Observed, not estimated

846ms average. Fast in production.

Agent Scoring Engine is checked daily against the live service.

Daily averagePeak 1124ms
Aug 20Today
Fastest day
679ms
Slowest day
1124ms
14-day trend
Slowing+10%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 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 Scoring Engine, so you can see the experience inside your AI.

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

Agent Scoring Engine Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_pxy20XdHnsTrdCZB8wc0Ck1kM4p7yyqCZvVt0KgF/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 Scoring Engine capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "agent-scoring-ranking-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_pxy20XdHnsTrdCZB8wc0Ck1kM4p7yyqCZvVt0KgF/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 Scoring Engine owners hand off.

This MCP is essential for ML Engineers, AI Architects, and Data Scientists who manage multiple autonomous agents. If you need to compare several AI models or agents and determine which one is truly optimal, this capability gives you the mathematical backing you need. It moves you past simple averages and into deep performance analytics.

  • 01

    ML Engineer

    Uses the MCP to calculate composite scores and understand the trade-offs between accuracy and latency for model deployment.

  • 02

    AI Architect

    Determines the optimal agent combination by identifying the Pareto frontier across multiple system components.

  • 03

    Data Scientist

    Applies the scoring and ranking capabilities to benchmark different agent versions against established performance standards.

FAQ

Questions Agent Scoring Engine owners ask.

  • 01

    Does this MCP handle different types of metrics?

    Yes. It is designed to process diverse metrics like accuracy (a percentage), latency (milliseconds), and cost (currency). It normalizes them so you can compare them fairly in a single score.

  • 02

    What is the difference between scoring and ranking?

    Scoring gives you a single, quantitative number for an agent's performance. Ranking takes those scores and puts them into a clear, ordered list, showing you the top performers.

  • 03

    Can I prevent one metric from dominating the score?

    Absolutely. You use the capability to adjust weights for correlation, which prevents any single metric from unfairly skewing the final composite score.

  • 04

    What is the Pareto frontier?

    It's a mathematical concept that finds the optimal trade-off. It shows you the set of agents where you can't improve one metric (like speed) without sacrificing another (like accuracy).

  • 05

    Is this MCP suitable for real-time scoring?

    The MCP provides stable, reproducible rankings, making it ideal for batch evaluation workflows. The average latency is low, supporting frequent scoring runs.

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