Education
MW = Σ ProtParam average residue masses + H₂O, with ambiguity-code handling, kDa/mean-residue output, and unmodified-chain caveats. Educational use only.
Call this tool from your code in three languages.
curl -X POST 'http://127.0.0.1:3003/en/api/tools/protein-molecular-weight' \
-H 'Content-Type: application/json' \
-d '{"sequence":"MGSSHHHHHHSSGLVPRGSH","decimalPlaces":2}'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/protein-molecular-weight| Name | Type | Required | Description |
|---|---|---|---|
| sequence | textarea | Yes | One-letter amino-acid sequence (case-insensitive; spaces and * - . separators are ignored). |
| decimalPlaces | number | No | — |
JSON result
{
"key": {...},
"metadata": {
"key": "value"
},
"error": "Error message (optional)",
"message": "Notification message (optional)"
}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-protein-molecular-weight": {
"name": "protein-molecular-weight",
"description": "MW = Σ ProtParam average residue masses + H₂O, with ambiguity-code handling, kDa/mean-residue output, and unmodified-chain caveats. Educational use only.",
"baseUrl": "http://127.0.0.1:3003/mcp/sse?toolId=protein-molecular-weight",
"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": "protein-molecular-weight",
"arguments": {
"sequence": "MGSSHHHHHHSSGLVPRGSH",
"decimalPlaces": 2
}
}
}Questions or issues? Contact [email protected]