Data Processing
Limit numerical values to specified ranges by clipping, filtering, or marking out-of-bounds values. Perfect for data quality control, sensor data cleaning, business rule enforcement, and data preprocessing. Features: - Range clipping (clip values to min/max boundaries) - Range filtering (remove out-of-bounds rows) - Range marking (flag modified values) - Per-column range configuration - Automatic numeric column detection - Multiple handling strategies - Detailed modification reports - Statistical analysis of changes - Business rule enforcement Common Use Cases: - Sensor data validation and cleaning - Machine learning input preparation - Data quality control and validation - Business constraint enforcement - Outlier management and control - Data preprocessing pipelines
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/data-range-limiter' \
-H 'Content-Type: application/json' \
-d '{"inputData":"name,age,salary,temperature,score\nAlice,25,50000,36.5,85.2\nBob,32,75000,38.1,92.7\nCharlie,28,60000,37.2,78.9","rangeConfiguration":"","targetColumns":"age, salary, temperature\n\nLeave empty to auto-detect numeric columns","handlingStrategy":"clip","autoDetectRanges":false,"preserveOriginal":false,"markModified":true,"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-range-limiter| Name | Type | Required | Description |
|---|---|---|---|
| inputData | textarea | Yes | CSV data with headers and numeric values to be processed |
| rangeConfiguration | textarea | Yes | JSON object specifying min/max ranges for each column. Example: {"age": {"min": 18, "max": 65}} |
| targetColumns | textarea | No | Specify which columns to apply range limits to. Leave empty to auto-detect numeric columns. |
| handlingStrategy | select | No | — |
| autoDetectRanges | checkbox | No | Automatically suggest reasonable ranges based on data distribution |
| preserveOriginal | checkbox | No | Keep original values with "_original" suffix |
| markModified | checkbox | No | Add flags to indicate which values were modified |
| includeStatistics | checkbox | No | Generate detailed statistics about modifications |
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-range-limiter": {
"name": "data-range-limiter",
"description": "Limit numerical values to specified ranges by clipping, filtering, or marking out-of-bounds values. Perfect for data quality control, sensor data cleaning, business rule enforcement, and data preprocessing.\n\nFeatures:\n- Range clipping (clip values to min/max boundaries)\n- Range filtering (remove out-of-bounds rows)\n- Range marking (flag modified values)\n- Per-column range configuration\n- Automatic numeric column detection\n- Multiple handling strategies\n- Detailed modification reports\n- Statistical analysis of changes\n- Business rule enforcement\n\nCommon Use Cases:\n- Sensor data validation and cleaning\n- Machine learning input preparation\n- Data quality control and validation\n- Business constraint enforcement\n- Outlier management and control\n- Data preprocessing pipelines",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=data-range-limiter",
"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-range-limiter",
"arguments": {
"inputData": "name,age,salary,temperature,score\nAlice,25,50000,36.5,85.2\nBob,32,75000,38.1,92.7\nCharlie,28,60000,37.2,78.9",
"rangeConfiguration": "",
"targetColumns": "age, salary, temperature\n\nLeave empty to auto-detect numeric columns",
"handlingStrategy": "clip",
"autoDetectRanges": false,
"preserveOriginal": false,
"markModified": true,
"includeStatistics": true
}
}
}Questions or issues? Contact [email protected]