Fitness
Calculate Training Stress Score (TSS) for workout intensity and duration
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/training-stress-score' \
-H 'Content-Type: application/json' \
-d '{"intensityFactor":0.75,"duration":60,"ftp":null}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/training-stress-score| Name | Type | Required | Description |
|---|---|---|---|
| intensityFactor | number | Yes | — |
| duration | number | Yes | — |
| ftp | number | No | — |
JSON result
{
"key": {...},
"metadata": {
"key": "value"
},
"error": "Error message (optional)",
"message": "Notification message (optional)"
}Add this tool to your Model Context Protocol server so AI agents can list and call it.
Add this block to your MCP client configuration:
{
"mcpServers": {
"elysiatools-training-stress-score": {
"name": "training-stress-score",
"description": "Calculate Training Stress Score (TSS) for workout intensity and duration",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=training-stress-score",
"command": "",
"args": [],
"env": {},
"isActive": true,
"type": "sse"
}
}
}After connecting to the SSE endpoint, list the exposed tools:
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}Invoke the tool by its id, passing arguments built from its parameters:
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "training-stress-score",
"arguments": {
"intensityFactor": 0.75,
"duration": 60,
"ftp": null
}
}
}Questions or issues? Contact [email protected]