Data Processing
Normalize numerical data using Min-Max scaling to transform values to a 0-1 range. Perfect for machine learning preprocessing, data analysis, and feature scaling. Features: - Min-Max scaling (0-1 normalization) - Custom range support (e.g., -1 to 1) - Multiple column selection - Automatic data type detection - Handles missing values - Preserves non-numeric columns - Statistical summary included Common Use Cases: - Machine learning feature preparation - Neural network input normalization - Data visualization preprocessing - Comparative analysis across different scales
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/data-normalizer-minmax' \
-H 'Content-Type: application/json' \
-d '{"inputData":"name,age,salary\nAlice,25,50000\nBob,30,75000\nCharlie,35,120000","targetColumns":"age, salary or name, email\n\nLeave empty to auto-detect numeric columns","outputRange":"0, 1","handleMissing":"skip","preserveOriginal":false,"decimalPlaces":4,"includeStatistics":true}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/data-normalizer-minmax| Name | Type | Required | Description |
|---|---|---|---|
| inputData | textarea | Yes | — |
| targetColumns | textarea | No | — |
| outputRange | text | No | — |
| handleMissing | select | No | — |
| preserveOriginal | checkbox | No | — |
| decimalPlaces |
| number |
| No |
| — |
| includeStatistics | checkbox | No | — |
Text result
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}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-data-normalizer-minmax": {
"name": "data-normalizer-minmax",
"description": "Normalize numerical data using Min-Max scaling to transform values to a 0-1 range. Perfect for machine learning preprocessing, data analysis, and feature scaling.\n\nFeatures:\n- Min-Max scaling (0-1 normalization)\n- Custom range support (e.g., -1 to 1)\n- Multiple column selection\n- Automatic data type detection\n- Handles missing values\n- Preserves non-numeric columns\n- Statistical summary included\n\nCommon Use Cases:\n- Machine learning feature preparation\n- Neural network input normalization\n- Data visualization preprocessing\n- Comparative analysis across different scales",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=data-normalizer-minmax",
"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": "data-normalizer-minmax",
"arguments": {
"inputData": "name,age,salary\nAlice,25,50000\nBob,30,75000\nCharlie,35,120000",
"targetColumns": "age, salary or name, email\n\nLeave empty to auto-detect numeric columns",
"outputRange": "0, 1",
"handleMissing": "skip",
"preserveOriginal": false,
"decimalPlaces": 4,
"includeStatistics": true
}
}
}Questions or issues? Contact [email protected]