Text Processing
Split text into individual words, with each word on a new line
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/word-separator' \
-H 'Content-Type: application/json' \
-d '{"textInput":"Enter your text here to split into words...","addLineNumbers":false,"sortByLength":false,"handleSpecialChars":true,"preserveOriginalCase":true,"includeEmptyLines":false}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/word-separator| Name | Type | Required | Description |
|---|---|---|---|
| textInput | textarea | Yes | — |
| addLineNumbers | checkbox | No | Number each word for easy reference |
| sortByLength | checkbox | No | Sort words by length (longest first) |
| handleSpecialChars | checkbox | No | Preserve URLs, emails, and other special text patterns |
| preserveOriginalCase | checkbox | No |
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-word-separator": {
"name": "word-separator",
"description": "Split text into individual words, with each word on a new line",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=word-separator",
"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": "word-separator",
"arguments": {
"textInput": "Enter your text here to split into words...",
"addLineNumbers": false,
"sortByLength": false,
"handleSpecialChars": true,
"preserveOriginalCase": true,
"includeEmptyLines": false
}
}
}Questions or issues? Contact [email protected]
| Keep original letter casing (upper/lower case) |
| includeEmptyLines | checkbox | No | Keep empty lines in the output |
Text result
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}