Science & Education
Rectangular-barrier WKB T ≈ e^(−2κa) vs exact transmission, reflection R = 1−T, and over-barrier partial reflection for electron, proton, or custom mass.
Call this tool from your code in three languages.
curl -X POST 'http://127.0.0.1:3003/en/api/tools/tunneling-probability' \
-H 'Content-Type: application/json' \
-d '{"particle":"electron","customMass":0,"barrierHeight":1,"barrierWidth":1,"energy":0.5}'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/tunneling-probability| Name | Type | Required | Description |
|---|---|---|---|
| particle | select | Yes | — |
| customMass | number | No | — |
| barrierHeight | number | Yes | — |
| barrierWidth | number | Yes | — |
| energy | number | Yes | — |
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-tunneling-probability": {
"name": "tunneling-probability",
"description": "Rectangular-barrier WKB T ≈ e^(−2κa) vs exact transmission, reflection R = 1−T, and over-barrier partial reflection for electron, proton, or custom mass.",
"baseUrl": "http://127.0.0.1:3003/mcp/sse?toolId=tunneling-probability",
"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": "tunneling-probability",
"arguments": {
"particle": "electron",
"customMass": 0,
"barrierHeight": 1,
"barrierWidth": 1,
"energy": 0.5
}
}
}Questions or issues? Contact [email protected]
Text result
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}