Agent Resource Fairness Scheduler Connector for AI agents.
3 live capabilities
Deterministic resource scheduling for multi-agent token and compute workloads
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Why people use Agent Resource Fairness Scheduler
Stop agent starvation with Agent Resource Fairness Scheduler
With this MCP, you stop guessing. You define the weights, and the system handles the math. You get a predictable, fair distribution where the most important work always moves forward, and you can see exactly how much headroom you have left.
What Vinkius changes
You get a predictable, fair way to run multiple agents without one task accidentally killing the rest.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,400+ Connectors
- Real-world use case 01
Preventing high-priority task starvation
An engineer has a critical monitoring agent and several low-priority data scraping agents.
- Real-world use case 02
Predicting latency in agent swarms
A developer needs to know if a sudden burst of 500 requests will crash their budget.
- Real-world use case 03
Managing multi-tenant agent pools
A platform provider uses weighted allocation to ensure different customers get their promised share of tokens without one user's heavy usage affecting everyone else.
Complete set · 3capabilities
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.
01—03
3 capabilities in this set.
Part of 3 available through Agent Resource Fairness Scheduler.
- 01 Capability
Calculate resource allocation
Calculates the exact token and compute split for all agents based on their assigned priorities. It turns total capacity into a precise distribution map.
- 02 Capability
Estimate queue metrics
Predicts how long queues will take to drain and the cost of preempting tasks. This helps you plan for system latency and overhead.
- 03 Capability
Analyze system health
Evaluates the current state of the system for fairness and starvation issues. It identifies if priority inversion is occurring in your agent pool.
Set up in minutes
One URL. Then ask Agent Resource Fairness Scheduler to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Agent Resource Fairness Scheduler from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Agent Resource Fairness Scheduler, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Agent Resource Fairness Scheduler for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Agent Resource Fairness Scheduler URL.
- Step 03
Save and start
Save the connection and enable Agent Resource Fairness Scheduler in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-resource-fairness-scheduler": {
"url": "https://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Agent Resource Fairness Scheduler
Open Agent mode in chat and ask: "Using Agent Resource Fairness Scheduler, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-resource-fairness-scheduler": {
"url": "https://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Agent Resource Fairness Scheduler
Ask Copilot: "Using Agent Resource Fairness Scheduler, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-resource-fairness-scheduler": {
"url": "https://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Agent Resource Fairness Scheduler
Open Cascade and ask: "Using Agent Resource Fairness Scheduler, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-resource-fairness-scheduler": {
"url": "https://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Agent Resource Fairness Scheduler
Ask Cline: "Using Agent Resource Fairness Scheduler, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add agent-resource-fairness-scheduler --transport http "https://edge.vinkius.com/vk_preview_N4XhWdH8YrrAB6beib6DSdaMQ1hBgnOVd2fR3toU/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Agent Resource Fairness Scheduler
Ask Claude: "Using Agent Resource Fairness Scheduler, show me...". 3 tools are ready
Where the request belongs
Work Agent Resource Fairness Scheduler can move forward.
This is for engineers and platform architects building multi-agent systems where resource contention is a constant headache.
AI Platform Engineer
Managing the underlying compute and token budgets for large-scale agent deployments.
LLM Ops Specialist
Ensuring reliable throughput and preventing agent starvation during peak usage periods.
System Architect
Designing deterministic scheduling logic for complex, multi-tenant agent environments.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse Connectors
Load Balancer Distributor
Deterministic simulation engine for evaluating load balancing algorithms.
Priority Queue with Aging Scheduler
A deterministic scheduler that manages task execution using priority-based queues with an anti-starvation aging mechanism.
Agent Parallel Execution Optimizer
Optimize task distribution and efficiency metrics for agent swarms.
Agent Load Balancer Calculator
Deterministic load balancing engine for distributing request rates across agent instances.
Priority Inversion Detector
Detect and resolve priority inversion in real-time systems.
Rate Limiter State Calculator
Deterministic engine for evaluating Token Bucket, Leaky Bucket, and sliding window rate limiting states.
Bring your own AI
Change the model, client or framework. Keep Agent Resource Fairness Scheduler connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
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LibreChat -
TypingMind -
Chorus -
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LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Agent Resource Fairness Scheduler.
The practical details behind the request, access and result.
How does the Agent Resource Fairness Scheduler prevent agent starvation?
It uses weighted fair queuing to ensure that even low-priority agents are guaranteed a specific slice of the resource pool, preventing high-priority tasks from completely blocking them.
Can I use the Agent Resource Fairness Scheduler to predict my token usage?
Yes. You can use the predictive capabilities to estimate how long queues will take to clear and how much compute is required, helping you manage your budget and latency.
Does the Agent Resource Fairness Scheduler work with any AI client?
It works with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code, as long as they are connected through a platform like Vinkius.
How does the Agent Resource Fairness Scheduler handle priority inversion?
The system monitors for priority inversion and provides health metrics so you can identify and fix instances where a low-priority task is inadvertently blocking a high-priority one.
What is the benefit of using the Agent Resource Fairness Scheduler for multi-agent systems?
It provides deterministic control over how agents share limited resources, ensuring that your most critical tasks always have the compute and tokens they need to succeed.
One connection away
Give your agent a direct line to Agent Resource Fairness Scheduler.
Connect Agent Resource Fairness Scheduler once. Keep it beside 6,400+ managed Connectors when the next task needs more.
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