Does this MCP calculate the cost in dollars?

It calculates the usage metrics and the financial burden based on the token counts and subscription levels you provide. It gives you the data needed to calculate the dollar cost, but you input the final pricing variables.

What kind of data does this MCP need?

It requires usage data, specifically token counts, feature usage breakdowns, and details about the subscription tiers you offer.

Is this only for large companies?

No. If your SaaS product uses LLMs and you worry about token costs, this MCP helps. It's for any team managing AI-driven services.

Can I use this with my existing analytics dashboard?

You feed the data from your dashboard into your AI client, and then your agent uses this MCP to perform the complex economic analysis on that data.

How can I calculate the cost of serving different user tiers?

You can use the get_tier_cost_analysis capability. It calculates the cost per user for each tier based on the total tokens, the price per million tokens, and the specific distribution of users and their usage within those tiers.

Can this capability help identify which features are most expensive?

Yes. The get_feature_efficiency_breakdown capability analyzes the total token load and provides a percentage breakdown for each feature, highlighting which parts of your application consume the most resources.

How does caching affect the calculated token usage?

The get_optimized_consumption_impact capability accounts for caching. By providing a cache hit ratio, the capability calculates the net tokens processed and the total savings percentage achieved through efficient retrieval.

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Connect AI SAAS Token Economics Engine to ChatGPT and Claude

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. Know exactly where your AI spending goes, down to the feature level.

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.

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 · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI SaaS Token Economics.

01
Get user consumption metrics
Provides high-level average usage statistics per user
02
Get feature efficiency breakdown
Analyzes how much each feature contributes to the total token load
03
Get optimized consumption impact
Estimates the savings gained from optimization and caching strategies
04
Get tier cost analysis
Calculates the financial burden of serving users across different subscription levels

Real work

What teams actually run

Pricing a new feature

Before launching a new summarization capability, you run a cost analysis to ensure the expected revenue covers the token cost.

Optimizing chat interfaces

You use the optimization impact capability to quantify how much token usage drops when you implement a better caching layer.

Evaluating enterprise plans

You test different subscription levels to see how the overall cost structure changes when moving from basic to enterprise users.

Debugging high usage spikes

When usage spikes, you run the feature breakdown to immediately see if the cost is concentrated in one specific component.

One connector, every AI

AI SaaS Token Economics 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 AI SaaS Token Economics 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

867ms average. Fast in production.

AI SaaS Token Economics is checked daily against the live service.

Daily averagePeak 1016ms

Oct 3Today

Fastest day: 661ms
Slowest day: 1016ms
14-day trend: Slowing+5%

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 AI SaaS Token Economics, so you can see the experience inside your AI.

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

AI SaaS Token Economics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_zKKuH4aPEyAjOvsxHHhMD18JRRZ4PINEAX5x4F5q/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 — AI SaaS Token Economics capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "ai-saas-token-economics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_zKKuH4aPEyAjOvsxHHhMD18JRRZ4PINEAX5x4F5q/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 AI SaaS Token Economics in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AI SaaS Token Economics owners hand off.

Product Managers, CTOs, and Finance Analysts use this MCP to move beyond simple usage reports. They need to connect raw token data to actual dollar costs. This allows them to build pricing models that are both profitable and scalable for growing AI platforms.

01
Product Manager
Determines which features to prioritize by understanding their true token cost.
02
CTO / Head of Engineering
Uses it to guide engineering efforts toward cost-saving optimizations like caching.
03
Finance Analyst
Builds and stress-tests subscription models to ensure revenue covers variable LLM costs.

FAQ

Questions AI SaaS Token Economics owners ask.

01
Does this MCP calculate the cost in dollars?
It calculates the usage metrics and the financial burden based on the token counts and subscription levels you provide. It gives you the data needed to calculate the dollar cost, but you input the final pricing variables.
02
What kind of data does this MCP need?
It requires usage data, specifically token counts, feature usage breakdowns, and details about the subscription tiers you offer.
03
Is this only for large companies?
No. If your SaaS product uses LLMs and you worry about token costs, this MCP helps. It's for any team managing AI-driven services.
04
Can I use this with my existing analytics dashboard?
You feed the data from your dashboard into your AI client, and then your agent uses this MCP to perform the complex economic analysis on that data.
05
How can I calculate the cost of serving different user tiers?
You can use the get_tier_cost_analysis capability. It calculates the cost per user for each tier based on the total tokens, the price per million tokens, and the specific distribution of users and their usage within those tiers.
06
Can this capability help identify which features are most expensive?
Yes. The get_feature_efficiency_breakdown capability analyzes the total token load and provides a percentage breakdown for each feature, highlighting which parts of your application consume the most resources.
07
How does caching affect the calculated token usage?
The get_optimized_consumption_impact capability accounts for caching. By providing a cache hit ratio, the capability calculates the net tokens processed and the total savings percentage achieved through efficient retrieval.

Explore

More in Analytics

Connect AI SaaS Token Economics 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.

01-04

Get user consumption metrics

Get feature efficiency breakdown

Get optimized consumption impact

Get tier cost analysis

What teams actually run

Pricing a new feature

Optimizing chat interfaces

Evaluating enterprise plans

Debugging high usage spikes

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

AI SaaS Token Economics Connector

Claude Desktop

Product Manager

CTO / Head of Engineering

Finance Analyst

Does this MCP calculate the cost in dollars?

What kind of data does this MCP need?

Is this only for large companies?

Can I use this with my existing analytics dashboard?

How can I calculate the cost of serving different user tiers?

Can this capability help identify which features are most expensive?

How does caching affect the calculated token usage?

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