Science & Education
p_i = x_i·p_i* for ideal solutions, with total pressure and vapour-phase composition for binary mixtures.
Call this tool from your code in three languages.
curl -X POST 'http://127.0.0.1:3003/en/api/tools/raoult-law-calculator' \
-H 'Content-Type: application/json' \
-d '{"mode":"binary","xA":0.5,"pAStar":95.1,"pBStar":28.4,"x":0.85,"pStar":23.76}'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/raoult-law-calculator| Name | Type | Required | Description |
|---|---|---|---|
| mode | select | Yes | — |
| xA | number | Yes | — |
| pAStar | number | Yes | — |
| pBStar | number | Yes | — |
| x | number | No | — |
| pStar | 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-raoult-law-calculator": {
"name": "raoult-law-calculator",
"description": "p_i = x_i·p_i* for ideal solutions, with total pressure and vapour-phase composition for binary mixtures.",
"baseUrl": "http://127.0.0.1:3003/mcp/sse?toolId=raoult-law-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": "raoult-law-calculator",
"arguments": {
"mode": "binary",
"xA": 0.5,
"pAStar": 95.1,
"pBStar": 28.4,
"x": 0.85,
"pStar": 23.76
}
}
}Questions or issues? Contact [email protected]
| No |
| — |
Text result
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}