Data Processing
Paste one or two columns of numbers and get the complete descriptive suite — mean/median/mode, sample and population variance, type-7 quartiles and percentiles, MAD, adjusted skewness and kurtosis, Tukey outliers — plus covariance, Pearson r, tie-corrected Spearman rho and least-squares regression for two columns.
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/general-statistics-calculator' \
-H 'Content-Type: application/json' \
-d '{"numbers":"2 4 4 4 5 5 7 9","datasetB":"","varianceBasis":"sample","decimalPlaces":4,"showOutliers":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/general-statistics-calculator| Name | Type | Required | Description |
|---|---|---|---|
| numbers | textarea | Yes | — |
| datasetB | textarea | No | — |
| varianceBasis | select | Yes | — |
| decimalPlaces | number | No | — |
| showOutliers | checkbox | No | — |
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-general-statistics-calculator": {
"name": "general-statistics-calculator",
"description": "Paste one or two columns of numbers and get the complete descriptive suite — mean/median/mode, sample and population variance, type-7 quartiles and percentiles, MAD, adjusted skewness and kurtosis, Tukey outliers — plus covariance, Pearson r, tie-corrected Spearman rho and least-squares regression for two columns.",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=general-statistics-calculator",
"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": "general-statistics-calculator",
"arguments": {
"numbers": "2 4 4 4 5 5 7 9",
"datasetB": "",
"varianceBasis": "sample",
"decimalPlaces": 4,
"showOutliers": true
}
}
}HTML result
{
"result": "<div>Processed HTML content</div>",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}Questions or issues? Contact [email protected]