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Data Processing

Min-Max Normalizer

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

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Quick start

Call this tool from your code in three languages.

cURL
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":false}'

API reference

Send a POST request with your inputs as JSON. File parameters require a separate upload first.

Endpoint

HTTP
POST https://api.elysiatools.com/en/api/tools/data-normalizer-minmax

Parameters

NameTypeRequiredDescription
inputDatatextareaYes—
targetColumnstextareaNo—
outputRangetextNo—
handleMissingselectNo—
preserveOriginalcheckboxNo—
decimalPlaces

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number
No
—
includeStatisticscheckboxNo—

Response format

Text result

JSON
{
  "result": "Processed text content",
  "error": "Error message (optional)",
  "message": "Notification message (optional)",
  "metadata": {
    "key": "value"
  }
}

MCP integration

Add this tool to your Model Context Protocol server so AI agents can list and call it.

Server configuration

Add this block to your MCP client configuration:

mcp.json
{
  "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"
    }
  }
}

List available tools

After connecting to the SSE endpoint, list the exposed tools:

tools/list
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

Call this tool

Invoke the tool by its id, passing arguments built from its parameters:

tools/call
{
  "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": false
}
  }
}
Chain multiple tools in one session with a comma-separated toolId list, e.g. /mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp (max 20).

Questions or issues? Contact [email protected]

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