Math & Numbers
Calculate posterior probability P(A given B) using prior, likelihood, and false-positive rate
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/bayes-theorem-calculator' \
-H 'Content-Type: application/json' \
-d '{"priorProbability":1,"likelihood":99,"falsePositiveRate":5,"inputScale":"percent","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/bayes-theorem-calculator| Name | Type | Required | Description |
|---|---|---|---|
| priorProbability | number | Yes | — |
| likelihood | number | Yes | — |
| falsePositiveRate | number | Yes | — |
| inputScale | select | No | — |
| decimalPlaces | number | 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-bayes-theorem-calculator": {
"name": "bayes-theorem-calculator",
"description": "Calculate posterior probability P(A given B) using prior, likelihood, and false-positive rate",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=bayes-theorem-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": "bayes-theorem-calculator",
"arguments": {
"priorProbability": 1,
"likelihood": 99,
"falsePositiveRate": 5,
"inputScale": "percent",
"decimalPlaces": 4
}
}
}Questions or issues? Contact [email protected]
JSON result
{
"key": {...},
"metadata": {
"key": "value"
},
"error": "Error message (optional)",
"message": "Notification message (optional)"
}