Text Processing
从粘贴文本、混合分隔符、键值行或 HTML 中推断表格,并导出 CSV、JSON 和 Markdown。
用三种语言从你的代码中调用此工具。
curl -X POST 'https://api.elysiatools.com/zh/api/tools/messy-text-to-structured-data-workbench' \
-H 'Content-Type: application/json' \
-d '{"textInput":"name\tage\tactive\nAda\t37\ttrue\nLinus\t5\tfalse","inputMode":"auto","delimiter":"","headerMode":"auto","trimCells":true,"useAI":false}'以 JSON 形式 POST 提交输入参数。文件类型参数需先单独上传。
POST https://api.elysiatools.com/zh/api/tools/messy-text-to-structured-data-workbench| 参数名 | 类型 | 必填 | 说明 |
|---|---|---|---|
| textInput | textarea | 是 | — |
| inputMode | select | 否 | — |
| delimiter | text | 否 | — |
| headerMode | select | 否 | — |
| trimCells | checkbox | 否 | — |
| useAI | checkbox |
将此工具加入你的 Model Context Protocol 服务,让 AI 智能体可以列出并调用它。
将以下内容加入你的 MCP 客户端配置:
{
"mcpServers": {
"elysiatools-messy-text-to-structured-data-workbench": {
"name": "messy-text-to-structured-data-workbench",
"description": "从粘贴文本、混合分隔符、键值行或 HTML 中推断表格,并导出 CSV、JSON 和 Markdown。",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=messy-text-to-structured-data-workbench",
"command": "",
"args": [],
"env": {},
"isActive": true,
"type": "sse"
}
}
}连接到 SSE 端点后,列出已开放的工具:
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}通过工具 id 调用,参数由其参数表构建:
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "messy-text-to-structured-data-workbench",
"arguments": {
"textInput": "name\tage\tactive\nAda\t37\ttrue\nLinus\t5\tfalse",
"inputMode": "auto",
"delimiter": "",
"headerMode": "auto",
"trimCells": true,
"useAI": false
}
}
}有问题或反馈?请联系 [email protected]
| 否 |
| — |
JSON 结果
{
"key": {...},
"metadata": {
"key": "value"
},
"error": "Error message (optional)",
"message": "Notification message (optional)"
}