Science & Education
Δx·Δp ≥ ℏ/2: minimum Δp from Δx, minimum Δx from Δp, or a pair check with satisfaction ratio. Units m–pm and kg·m/s / g·cm/s / eV/c; optional mass derives Δv.
Call this tool from your code in three languages.
curl -X POST 'http://127.0.0.1:3003/en/api/tools/uncertainty-principle-calculator' \
-H 'Content-Type: application/json' \
-d '{"mode":"dp","dx":100,"dxUnit":"pm","dp":0,"dpUnit":"kgms","mass":9.1093837015e-31}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST http://127.0.0.1:3003/en/api/tools/uncertainty-principle-calculator| Name | Type | Required | Description |
|---|---|---|---|
| mode | select | Yes | — |
| dx | number | No | — |
| dxUnit | select | Yes | — |
| dp | number | No | — |
| dpUnit | select | Yes | — |
| mass | number |
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-uncertainty-principle-calculator": {
"name": "uncertainty-principle-calculator",
"description": "Δx·Δp ≥ ℏ/2: minimum Δp from Δx, minimum Δx from Δp, or a pair check with satisfaction ratio. Units m–pm and kg·m/s / g·cm/s / eV/c; optional mass derives Δv.",
"baseUrl": "http://127.0.0.1:3003/mcp/sse?toolId=uncertainty-principle-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": "uncertainty-principle-calculator",
"arguments": {
"mode": "dp",
"dx": 100,
"dxUnit": "pm",
"dp": 0,
"dpUnit": "kgms",
"mass": 9.1093837015e-31
}
}
}Questions or issues? Contact [email protected]
| No |
| — |
Text result
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}