Text Processing
识别文本中的常见个人信息,并用稳定、可审计的伪名替换重复实体,全程无需上传模型。
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/consistent-pseudonym-text-anonymizer' \
-H 'Content-Type: application/json' \
-d '{"textInput":"Email [email protected] and [email protected]; phone 13800138000.","entityTypes":["email","phone"],"replacementMode":"label","includeMapping":true,"seed":"demo"}'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/consistent-pseudonym-text-anonymizer| 参数名 | 类型 | 必填 | 说明 |
|---|---|---|---|
| textInput | textarea | 是 | — |
| entityTypes | select | 否 | — |
| replacementMode | select | 否 | — |
| includeMapping | checkbox | 否 | — |
| seed | text | 否 | — |
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-consistent-pseudonym-text-anonymizer": {
"name": "consistent-pseudonym-text-anonymizer",
"description": "识别文本中的常见个人信息,并用稳定、可审计的伪名替换重复实体,全程无需上传模型。",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=consistent-pseudonym-text-anonymizer",
"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": "consistent-pseudonym-text-anonymizer",
"arguments": {
"textInput": "Email [email protected] and [email protected]; phone 13800138000.",
"entityTypes": [
"email",
"phone"
],
"replacementMode": "label",
"includeMapping": true,
"seed": "demo"
}
}
}有问题或反馈?请联系 [email protected]
{
"key": {...},
"metadata": {
"key": "value"
},
"error": "Error message (optional)",
"message": "Notification message (optional)"
}