Data Analysis
Advanced regression analysis tool for performing linear regression analysis, calculating regression statistics, and making predictions. Perfect for statistical modeling, trend analysis, forecasting, and understanding relationships between variables. Features: - Simple linear regression (y = mx + b) - Multiple linear regression support - Regression coefficients calculation - Statistical significance testing - R-squared and adjusted R-squared - Residual analysis and diagnostics - Prediction intervals and confidence intervals - Outlier detection in regression - Model validation metrics - Visual regression diagnostics - Data transformation support Common Use Cases: - Sales forecasting and trend analysis - Financial modeling and risk assessment - Scientific research and hypothesis testing - Quality control and process optimization - Marketing analytics and ROI analysis - Medical and biological research
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/regression-analyzer' \
-H 'Content-Type: application/json' \
-d '{"inputData":"sales,advertising,price,season\n1500,200,29.99,1\n1800,250,27.99,2\n2100,300,24.99,1\n1900,280,26.99,2\n2400,350,22.99,1","targetColumn":"sales","featureColumns":"advertising, price, season\n\nLeave empty to auto-detect numeric columns","regressionType":"multiple","confidenceLevel":"0.95","handleMissing":"remove","outlierMethod":"none","includeIntercept":true,"standardizeFeatures":false,"generatePredictions":false,"predictionData":"advertising, price, season\n320,21.99,1\n280,25.99,2","includeDiagnostics":true,"decimalPlaces":4}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/regression-analyzer| Name | Type | Required | Description |
|---|---|---|---|
| inputData | textarea | Yes | — |
| targetColumn | text | Yes | — |
| featureColumns | textarea | No | — |
| regressionType | select | No | — |
| confidenceLevel | select | No | — |
| handleMissing | select | No | — |
| outlierMethod | select | No | — |
| includeIntercept | checkbox | No | — |
| standardizeFeatures | checkbox | No | — |
| generatePredictions | checkbox | No | — |
| predictionData | textarea | No | CSV data for making predictions (must include same feature columns as training data) |
| includeDiagnostics | checkbox | No | — |
| decimalPlaces | number | No | Number of decimal places for regression coefficients and statistics |
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-regression-analyzer": {
"name": "regression-analyzer",
"description": "Advanced regression analysis tool for performing linear regression analysis, calculating regression statistics, and making predictions. Perfect for statistical modeling, trend analysis, forecasting, and understanding relationships between variables.\n\nFeatures:\n- Simple linear regression (y = mx + b)\n- Multiple linear regression support\n- Regression coefficients calculation\n- Statistical significance testing\n- R-squared and adjusted R-squared\n- Residual analysis and diagnostics\n- Prediction intervals and confidence intervals\n- Outlier detection in regression\n- Model validation metrics\n- Visual regression diagnostics\n- Data transformation support\n\nCommon Use Cases:\n- Sales forecasting and trend analysis\n- Financial modeling and risk assessment\n- Scientific research and hypothesis testing\n- Quality control and process optimization\n- Marketing analytics and ROI analysis\n- Medical and biological research",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=regression-analyzer",
"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": "regression-analyzer",
"arguments": {
"inputData": "sales,advertising,price,season\n1500,200,29.99,1\n1800,250,27.99,2\n2100,300,24.99,1\n1900,280,26.99,2\n2400,350,22.99,1",
"targetColumn": "sales",
"featureColumns": "advertising, price, season\n\nLeave empty to auto-detect numeric columns",
"regressionType": "multiple",
"confidenceLevel": "0.95",
"handleMissing": "remove",
"outlierMethod": "none",
"includeIntercept": true,
"standardizeFeatures": false,
"generatePredictions": false,
"predictionData": "advertising, price, season\n320,21.99,1\n280,25.99,2",
"includeDiagnostics": true,
"decimalPlaces": 4
}
}
}Questions or issues? Contact [email protected]