Stat Scaling Calculator MCP for AI. Define how attributes grow from Level 1 to Max.

Q: How can I generate a level-by-level attribute breakdown?

Use the computeprogressiontable tool by providing your base stat, target stat, maximum level, and desired curve type.

Q: How do I identify power spikes in my progression?

The analyzegrowthvelocity tool calculates the change in value between consecutive levels, making it easy to spot sudden jumps or plateaus.

Q: Can I compare different scaling archetypes side-by-side?

Yes. The comparescalingstrategies tool aligns multiple configurations onto a single dataset for direct comparison.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

Stat Scaling Calculator helps game designers build mathematically sound attribute progression curves. Determine how core stats like Strength, Health, or Mana change from character level one to max level.

Generate detailed breakdowns for linear, exponential, and S-curves, ensuring your combat balance holds up through every expansion pack.

What your AI can do

Compare scaling strategies

Produces a unified dataset for visual comparison of different scaling configurations.

Analyze growth velocity

Calculates the incremental change in an attribute's value between consecutive levels.

Compute progression table

Generates a complete step-by-step breakdown of an attribute's value for every level.

Model Attribute Progression

Generate complete level-by-level breakdowns for core attributes like Strength or Mana.

Identify Growth Discrepancies

Calculate the exact increase, or delta, in a stat's value between any two consecutive levels to flag unintended power spikes.

Compare Scaling Models

View multiple attribute growth configurations on one unified dataset for quick side-by-side comparison.

Ask an AI about this

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AI Agent

Stat Scaling Calculator with 3 Tools

These tools let you mathematically model how any character attribute evolves over time, helping you maintain game balance across all levels.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Stat Scaling Calculator on Vinkius

Compare Scaling Strategies

Produces a unified dataset for visual comparison of different scaling configurations.

Analyze Growth Velocity

Calculates the incremental change in an attribute's value between consecutive levels.

Compute Progression Table

Generates a complete step-by-step breakdown of an attribute's value for every level.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The Stat Scaling Calculator integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "stat-scaling-calculator": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the Stat Scaling Calculator tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"stat-scaling-calculator": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with Stat Scaling Calculator, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Stat Scaling Calculator. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Managed infra

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No stored credentials

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Policy on every call

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Token Compression

~60% cost reduction

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

The Old Way of Balancing Attributes

Today, balancing attributes means opening massive spreadsheets. You manually chart the progression: Level 1 needs 5 points, Level 2 needs 7, Level 3 needs 9. If you're checking a whole class—say, comparing Strength to Constitution—you have to create separate tabs for every single stat, and then copy-paste data just to put them side by side.

With this MCP, you bypass the spreadsheet entirely. You define your starting parameters and curve type once. The output gives you clean, structured data that lets you model complex growth patterns in seconds. What you get is a unified view of statistical progression.

Seeing Multiple Curves with `compare_scaling_strategies`

Previously, comparing two scaling strategies meant running two separate calculations and then manually finding ways to overlay the data—which was often messy and difficult to read. You could only compare simple linear growths against each other.

Now, `compare_scaling_strategies` generates a single dataset optimized for visual comparison of multiple configurations. It makes it easy to tell at a glance which scaling model feels balanced compared to another.

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What your AI can actually do with this

Designing a successful RPG means making sure the power curve feels consistent. It's not enough that stats increase; you need them to increase in a way that makes sense when players hit level 50 versus when they start at level 1. This MCP gives designers precise math tools to model how attributes evolve over time, letting you define everything from simple linear growth to complex exponential jumps.

You can generate detailed, step-by-step tables for any attribute and test multiple scaling methods side by side. If you're juggling dozens of stats and trying to predict unintended power spikes before playtesting, this is what you need. For a full picture of how your entire development pipeline runs—from asset creation to balancing checks—Vinkius AI Analytics shows you exactly what every agent did, which tools ran, what data flowed through, and how the budget is being spent.

It's pure, verifiable math for complex game systems.

Built · Hosted · Managed by Vinkius Stat Scaling Calculator - Game Attribute Progression Tool

Server ID 019ed0fe-9664-71d7-a327-1b6ac7de6cd8

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

What Changes When You Connect

Avoid power creep. By running the analyze_growth_velocity tool, you pinpoint exactly where a stat jumps too hard between levels, letting you adjust the curve before testing even starts.

Visualize complex balance changes instantly. The compare_scaling_strategies tool lets you overlay five different attribute curves on one chart to see which feels best for your core gameplay loop.

Build reliable character sheets. Use compute_progression_table to get a full, level-by-level breakdown of every stat (Strength, Health, etc.), guaranteeing consistency across the entire game lifecycle.

Test multiple systems fast. You can rapidly cycle through different math models—exponential vs. linear—to see which curve best matches your desired difficulty ramp.

Pinpoint balance issues early. Don't wait for playtesting to find a stat that suddenly becomes overpowered; use this MCP to predict the spikes.

See it in action

01 01

The Mana Spike Problem

A designer noticed their Mage class could dump too much Mana at level 30, breaking the combat rhythm. They used analyze_growth_velocity to pinpoint that specific delta and adjusted the curve until the growth was gradual enough for a smoother experience.

02 02

Comparing Race Bonuses

A team needed to compare how much damage bonuses different racial classes received at max level. They used compare_scaling_strategies to put three separate, complex calculation curves onto one chart, making the balance decision obvious.

03 03

Building a New Core Stat

A game architect needed a new 'Focus' stat and had no idea how it should scale. They ran compute_progression_table with multiple curve types (S-curve, linear) to determine the best mathematical fit for their gameplay needs.

The honest tradeoffs

Using Spreadsheets

Anti-pattern

Manually calculating attribute progression across 50 levels in Excel. This is slow, requires dozens of formulas that break easily, and makes comparing curves impossible.

The Fix

Use compute_progression_table to generate the full data set programmatically. Then, use compare_scaling_strategies to visualize and compare three or more different models immediately.

Guessing the Delta

Anti-pattern

Assuming that because a stat increased by 5 at level 10, it should increase by 5 again at level 20. This ignores exponential growth patterns.

The Fix

Run analyze_growth_velocity to calculate the actual change between levels 10 and 20. The tool gives you the precise delta needed for accurate balance checks.

Over-engineering Formulas

Anti-pattern

Writing excessively complicated, nested formulas that are impossible to debug when a single variable changes.

The Fix

Let this MCP handle the math. Use compute_progression_table and feed it simple inputs (start/end values) and let the tool generate the clean, reproducible data.

When It Fits, When It Doesn't

Use this if your core problem is mathematical consistency: you need to prove that a stat's growth rate across 50 levels makes sense. You must check for power spikes or dips at specific breakpoints; analyze_growth_velocity handles this perfectly. Don't use it if you simply need to track current, fixed stats—a basic database lookup tool is enough. If your goal is comparing how three different systems (e.g., magic damage vs. physical damage) scale relative to each other over time, then the compare_scaling_strategies function is non-negotiable. It's built for comparative analysis, not just single-curve generation.

Questions you might have

How can I generate a level-by-level attribute breakdown? +

Use the compute_progression_table tool by providing your base stat, target stat, maximum level, and desired curve type.

How do I identify power spikes in my progression? +

The analyze_growth_velocity tool calculates the change in value between consecutive levels, making it easy to spot sudden jumps or plateaus.

Can I compare different scaling archetypes side-by-side? +

Yes. The compare_scaling_strategies tool aligns multiple configurations onto a single dataset for direct comparison.

What format should I use when running `compute_progression_table`? +

You must provide three parameters: a starting value, an end level, and the desired curve type (e.g., linear or exponential). The tool returns a structured list mapping every requested level to its precise calculated attribute score.

How do I interpret the output from `analyze_growth_velocity`? +

The delta value it provides is the direct numerical difference between an attribute's current level and the previous level. This metric shows exactly how much power increases at any given step, helping you pinpoint sudden jumps in stats.

If I have dozens of scaling options, can `compare_scaling_strategies` handle them? +

Yes, this MCP is designed to process large datasets. You input multiple configurations into a single request, and the tool generates one unified dataset suitable for side-by-side visual analysis.

What happens if I give invalid data types when using `compute_progression_table`? +

If you try to input non-numeric values or levels that are out of sequence, the tool sends a specific error message detailing the required data type. You just need to correct your inputs accordingly.

Do I need any special setup for my AI client to execute `compare_scaling_strategies`? +

No specialized installation is necessary. Since this MCP runs on Vinkius, you only connect your existing agent through the standard MCP protocol in compatible clients like Cursor or VS Code.

Connect to your AI in seconds.

Compare scaling strategies

Analyze growth velocity

Compute progression table

Stat Scaling Calculator with 3 Tools

Make your AI actually useful.

Compare Scaling Strategies

Analyze Growth Velocity

Compute Progression Table

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

The Old Way of Balancing Attributes

Seeing Multiple Curves with `compare_scaling_strategies`

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

The Mana Spike Problem

Comparing Race Bonuses

Building a New Core Stat

The honest tradeoffs

Using Spreadsheets

Guessing the Delta

Over-engineering Formulas

When It Fits, When It Doesn't

Questions you might have