Format Conversion
Encode and decode Base64 strings
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/base64-encoder' \
-H 'Content-Type: application/json' \
-d '{"textInput":"Enter text to encode/decode...","operation":"encode"}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/base64-encoder| Name | Type | Required | Description |
|---|---|---|---|
| textInput | textarea | Yes | — |
| operation | select | Yes | — |
Text result
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}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-base64-encoder": {
"name": "base64-encoder",
"description": "Encode and decode Base64 strings",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=base64-encoder",
"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": "base64-encoder",
"arguments": {
"textInput": "Enter text to encode/decode...",
"operation": "encode"
}
}
}Questions or issues? Contact [email protected]