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Data Analysis

Data Distribution Analyzer

Comprehensive data distribution analysis with normality tests, outlier detection, and goodness-of-fit assessments

text· Text resultOpen tool

Quick start

Call this tool from your code in three languages.

cURL
curl -X POST 'https://api.elysiatools.com/en/api/tools/distribution-analyzer' \
  -H 'Content-Type: application/json' \
  -d '{"dataInput":"Enter your data values separated by commas or new lines...\n\nExamples:\n- Normal: 50, 51, 49, 52, 48, 50, 51, 49, 50, 52\n- Skewed: 45, 48, 50, 52, 55, 58, 60, 65, 70, 80\n- Bimodal: 20, 25, 30, 35, 40, 60, 65, 70, 75, 80","dataFormat":"single","significanceLevel":"0.05","includeHistogram":true,"testNormality":true,"detectOutliers":true}'

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/distribution-analyzer

Parameters

NameTypeRequiredDescription
dataInputtextareaYes—
dataFormatselectYes—
significanceLevelselectYes—
includeHistogramcheckboxNoGenerate frequency distribution and percentile information
testNormalitycheckboxNoPerform Anderson-Darling, Shapiro-Wilk, and Jarque-Bera tests

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-distribution-analyzer": {
      "name": "distribution-analyzer",
      "description": "Comprehensive data distribution analysis with normality tests, outlier detection, and goodness-of-fit assessments",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=distribution-analyzer",
      "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": "distribution-analyzer",
    "arguments": {
  "dataInput": "Enter your data values separated by commas or new lines...\n\nExamples:\n- Normal: 50, 51, 49, 52, 48, 50, 51, 49, 50, 52\n- Skewed: 45, 48, 50, 52, 55, 58, 60, 65, 70, 80\n- Bimodal: 20, 25, 30, 35, 40, 60, 65, 70, 75, 80",
  "dataFormat": "single",
  "significanceLevel": "0.05",
  "includeHistogram": true,
  "testNormality": true,
  "detectOutliers": true
}
  }
}
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).
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© 2026 Elysia Tools. Developer documentation.

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detectOutlierscheckboxNoIdentify outliers using multiple methods (IQR, Z-score, and robust statistics)

Response format

Text result

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

Questions or issues? Contact [email protected]