How does this MCP handle rounding errors?

It uses the largest-remainder method to ensure that the sum of all allocated tokens exactly matches your total budget without leaving leftovers or overshooting.

Can I use this with any model?

Yes. You can use the analyze_utilization capability to check your budget against the specific context limits of whatever model your agent is currently using.

What is the difference between weighted distribution and simple splitting?

Weighted distribution allows you to give more tokens to critical roles, like a planner, while simple splitting would give every agent an equal amount.

How do I see how many tokens are left during a run?

You can use the get_pipeline_checkpoints capability to see a step-by-step view of how much budget has been used and how much remains.

Do I need to host this myself?

No. Vinkius hosts and manages the MCP for you. You just connect your client and start using the capabilities.

How does the capability handle rounding errors?

The capability uses the largest-remainder method. It first assigns the floor of the proportional allocation to each agent and then distributes the remaining tokens to those with the largest fractional parts.

Can I detect if an agent has too few tokens?

Yes, by using allocate_budget with the minimumViable parameter, the capability will return a flag if any agent's allocation falls below your specified threshold.

How do I track token usage during execution?

You can use get_pipeline_checkpoints to see a step-by-step breakdown of consumed tokens and the remaining budget after each agent in the sequence.

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Connect Token Budget Allocator to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Stop guessing how many tokens your agents actually need.

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.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Token Budget Allocator.

01
Allocate budget
This capability calculates the exact integer token count for every agent in your pipeline based on assigned weights.
02
Analyze utilization
Use this to check if your allocated budget fits within the specific context window limits of your models.
03
Get pipeline checkpoints
This capability provides a step-by-step breakdown of token consumption and remaining budget as your pipeline runs.

Real work

What teams actually run

Multi-Agent Orchestration

Distribute a fixed pool of tokens across a planner, researcher, and writer to ensure no single agent starves the others.

Cost and Resource Management

Set a hard limit on total tokens for a complex task and have the MCP divide it among the necessary steps.

Model Constraint Validation

Verify that a high-intensity reasoning task won't exceed the specific context window of a smaller model.

Pipeline Debugging

Use checkpoints to find exactly which agent in a long chain is consuming more tokens than expected.

One connector, every AI

Token Budget Allocator works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put Token Budget Allocator to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

888ms average. Fast in production.

Token Budget Allocator is checked daily against the live service.

Daily averagePeak 980ms

Oct 3Today

Fastest day: 703ms
Slowest day: 980ms
14-day trend: Slowing+25%

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 Token Budget Allocator, so you can see the experience inside your AI.

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

Token Budget Allocator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_DwkIE8IAmqcAEWoHXw2LpMQmVNhPBekovfmOdjLN/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — Token Budget Allocator capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "token-budget-allocator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_DwkIE8IAmqcAEWoHXw2LpMQmVNhPBekovfmOdjLN/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

Guided setup for Claude? Set up Token Budget Allocator in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Token Budget Allocator owners hand off.

This MCP is built for developers and engineers building complex, multi-step agentic workflows.

01
AI Engineers
They hand off pipeline architecture and weight definitions to the MCP to manage resource limits.
02
LLM Ops Specialists
They use the capability to monitor utilization and ensure pipelines don't crash due to context overflows.
03
Workflow Developers
They use the budget checkpoints to debug where token consumption is spiking in a sequence.

FAQ

Questions Token Budget Allocator owners ask.

01
How does this MCP handle rounding errors?
It uses the largest-remainder method to ensure that the sum of all allocated tokens exactly matches your total budget without leaving leftovers or overshooting.
02
Can I use this with any model?
Yes. You can use the analyze_utilization capability to check your budget against the specific context limits of whatever model your agent is currently using.
03
What is the difference between weighted distribution and simple splitting?
Weighted distribution allows you to give more tokens to critical roles, like a planner, while simple splitting would give every agent an equal amount.
04
How do I see how many tokens are left during a run?
You can use the get_pipeline_checkpoints capability to see a step-by-step view of how much budget has been used and how much remains.
05
Do I need to host this myself?
No. Vinkius hosts and manages the MCP for you. You just connect your client and start using the capabilities.
06
How does the capability handle rounding errors?
The capability uses the largest-remainder method. It first assigns the floor of the proportional allocation to each agent and then distributes the remaining tokens to those with the largest fractional parts.
07
Can I detect if an agent has too few tokens?
Yes, by using allocate_budget with the minimumViable parameter, the capability will return a flag if any agent's allocation falls below your specified threshold.
08
How do I track token usage during execution?
You can use get_pipeline_checkpoints to see a step-by-step breakdown of consumed tokens and the remaining budget after each agent in the sequence.

Explore

More in Optimization

Connect Token Budget Allocator to Claude, Cursor, ChatGPT & more

Your AI does the work. We keep it safe and sound.

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-03

Allocate budget

Analyze utilization

Get pipeline checkpoints

What teams actually run

Multi-Agent Orchestration

Cost and Resource Management

Model Constraint Validation

Pipeline Debugging

Building your own app? The connector is yours to use.

Token Budget Allocator Connector

Claude Desktop

AI Engineers

LLM Ops Specialists

Workflow Developers

How does this MCP handle rounding errors?

Can I use this with any model?

What is the difference between weighted distribution and simple splitting?

How do I see how many tokens are left during a run?

Do I need to host this myself?

How does the capability handle rounding errors?

Can I detect if an agent has too few tokens?

How do I track token usage during execution?

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