Data Analysis
Detect outliers in numerical data using various statistical methods including IQR, Z-score, and modified Z-score
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/outlier-detector' \
-H 'Content-Type: application/json' \
-d '{"dataInput":"Enter numerical data separated by delimiter...\n12.5, 15.2, 13.8, 45.6, 18.9, 16.1, 14.7, 17.3, 22.1","delimiter":"comma","customDelimiter":"Enter custom delimiter","detectionMethod":"iqr","sensitivity":1.5,"includeStatistics":true,"outputFormat":"summary"}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/outlier-detector| Name | Type | Required | Description |
|---|---|---|---|
| dataInput | textarea | Yes | — |
| delimiter | select | Yes | — |
| customDelimiter | text | No | — |
| detectionMethod | select | Yes | — |
| sensitivity | number | No | — |
| includeStatistics |
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-outlier-detector": {
"name": "outlier-detector",
"description": "Detect outliers in numerical data using various statistical methods including IQR, Z-score, and modified Z-score",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=outlier-detector",
"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": "outlier-detector",
"arguments": {
"dataInput": "Enter numerical data separated by delimiter...\n12.5, 15.2, 13.8, 45.6, 18.9, 16.1, 14.7, 17.3, 22.1",
"delimiter": "comma",
"customDelimiter": "Enter custom delimiter",
"detectionMethod": "iqr",
"sensitivity": 1.5,
"includeStatistics": true,
"outputFormat": "summary"
}
}
}Questions or issues? Contact [email protected]
| checkbox |
| No |
| — |
| outputFormat | select | Yes | — |
Text result
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}