Development
Run a safe, curated set of Lodash helpers on JSON input.
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/lodash-online-utility' \
-H 'Content-Type: application/json' \
-d '{"inputJson":"[1,2,3,4,5]","method":"chunk","argsJson":"[2]"}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/lodash-online-utility| Name | Type | Required | Description |
|---|---|---|---|
| inputJson | textarea | Yes | — |
| method | select | No | — |
| argsJson | textarea | 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-lodash-online-utility": {
"name": "lodash-online-utility",
"description": "Run a safe, curated set of Lodash helpers on JSON input.",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=lodash-online-utility",
"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": "lodash-online-utility",
"arguments": {
"inputJson": "[1,2,3,4,5]",
"method": "chunk",
"argsJson": "[2]"
}
}
}Questions or issues? Contact [email protected]