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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Agent Resource Fairness Scheduler with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Keep all your competing agents running fairly and predictably.

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 · 3 capabilities

The complete Agent Resource Fairness Scheduler capability set.

These are the exact actions your AI can choose when you ask it to work with Agent Resource Fairness Scheduler.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Agent Resource Fairness Scheduler.

  1. 01

    Calculate resource allocation

    Determine exact token and compute distribution for all agents based on priorities and requests

  2. 02

    Estimate queue metrics

    Predict future system behavior, including queue drain time and preemption costs

  3. 03

    Analyze system health

    Evaluate system state regarding fairness, starvation, and priority issues

Observed, not estimated

793ms average. Fast in production.

Agent Resource Fairness Scheduler is checked daily against the live service.

Daily averagePeak 973ms
Aug 20Today
Fastest day
644ms
Slowest day
973ms
14-day trend
Slowing+20%

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 Resource Fairness Scheduler, so you can see the experience inside your AI.

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

Agent Resource Fairness Scheduler Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/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 Resource Fairness Scheduler capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "agent-resource-fairness-scheduler-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/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 Resource Fairness Scheduler owners hand off.

This MCP is essential for developers building complex, multi-agent applications. If your system relies on many independent AI agents running concurrently, you need predictable resource management. It gives you the capabilities to guarantee that no single agent can monopolize the compute power.

  • 01

    MLOps Engineer

    Use this to monitor and guarantee that resource allocation remains stable under heavy load.

  • 02

    AI Architect

    Use this to design multi-agent workflows that require deterministic and fair resource sharing.

  • 03

    Software Developer

    Use this to build robust applications that won't fail or degrade when multiple services run simultaneously.

FAQ

Questions Agent Resource Fairness Scheduler owners ask.

  • 01

    What is Weighted Fair Queuing (WFQ)?

    WFQ is a resource management technique that ensures bandwidth is distributed fairly among multiple users or agents. It guarantees that each agent gets a share of resources based on its specific weight or priority, preventing any single agent from monopolizing the system.

  • 02

    Does this MCP handle token limits?

    Yes. It is designed to manage both token and compute capacity. You can use the calculate_resource_allocation capability to determine exactly how many tokens each agent receives based on its priority and the total available pool.

  • 03

    What is Jain's Fairness Index?

    It's a mathematical metric used by the MCP to measure how evenly resources are distributed. A score of 1.0 means perfect, absolute fairness across all competing agents.

  • 04

    Can I predict system slowdowns?

    Absolutely. The estimate_queue_metrics capability lets you predict future behavior, giving you metrics like queue drain time and preemption costs so you can plan for bottlenecks.

  • 05

    Is this MCP only for tokens?

    No. It manages both token capacity and compute capacity (measured in milliseconds). It treats them as two separate, limited resources that must be allocated fairly.

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