Use Weight Increment Calculator with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Calculates optimal weight increases for progressive overload.
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.
Complete set · 4 capabilities
The complete Weight Increment Calculator capability set.
These are the exact actions your AI can choose when you ask it to work with Weight Increment Calculator.
01-04
4 capabilities in this set.
Part of 4 available through Weight Increment Calculator.
- 01
Get recommended increment
Determines the ideal weight increase for the next training session
- 02
Validate plate combination
Checks if a specific weight increase can be physically achieved with the available equipment
- 03
Calculate progression percentage
Calculates how much the weight is increasing relative to the current load
- 04
Get microloading strategy
Provides specific small-scale increment options when standard increments are too large
One connector, every AI
Weight Increment Calculator 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.
Claude
ChatGPT
Gemini
Perplexity
Grok
Microsoft Copilot
Cursor
VS Code
Windsurf
JetBrains
Cline
LangChain
Vercel AI SDK
Lovable
Z.ai
Raycast
Qwen Code
Kimi Code
Le ChatBuilding your own app? The connector is yours to use.
You don't need a client to put Weight Increment Calculator 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.
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 Weight Increment Calculator, so you can see the experience inside your AI.
It does not authenticate your account with Weight Increment Calculator. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Weight Increment Calculator Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_76oQf8Lxdtt13cJst2jO0LpYLR9HD7fnKSeDWAs7/mcpClaude 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 — Weight Increment Calculator capabilities are ready to use.
{
"mcpServers": {
"weight-increment-calculator-mcp": {
"url": "https://edge.vinkius.com/vk_preview_76oQf8Lxdtt13cJst2jO0LpYLR9HD7fnKSeDWAs7/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? How to give Claude access to Weight Increment Calculator
FAQ
Questions Weight Increment Calculator owners ask.
- 01
How does the calculator determine the weight increase?
The get_recommended_increment capability calculates the increase by analyzing your experience level, gender, and whether the exercise is a compound or isolation movement.
- 02
Can I check if I have the right plates for a weight jump?
Yes, use the validate_plate_combination capability. You provide your current weight, the target increment, your available plates, and the bar weight to see if the jump is physically possible.
- 03
What is microloading?
Microloading is the use of very small weight increments to continue progressing when standard jumps are too large. You can find these options using get_microloading_strategy.
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