Text Processing
使用余弦相似度、杰卡德相似度和编辑距离等多种算法计算两段文本的相似度百分比
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/text-similarity-detector' \
-H 'Content-Type: application/json' \
-d '{"text1":"Enter the first text to compare...","text2":"Enter the second text to compare...","algorithm":"combined","caseSensitive":false,"ignoreWhitespace":true,"minWordLength":2}'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/text-similarity-detector| 参数名 | 类型 | 必填 | 说明 |
|---|---|---|---|
| text1 | textarea | 是 | — |
| text2 | textarea | 是 | — |
| algorithm | select | 是 | — |
| caseSensitive | checkbox | 否 | Treat uppercase and lowercase as different characters |
| ignoreWhitespace | checkbox | 否 | Remove extra spaces, tabs, and newlines before comparison |
| minWordLength |
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-text-similarity-detector": {
"name": "text-similarity-detector",
"description": "使用余弦相似度、杰卡德相似度和编辑距离等多种算法计算两段文本的相似度百分比",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=text-similarity-detector",
"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": "text-similarity-detector",
"arguments": {
"text1": "Enter the first text to compare...",
"text2": "Enter the second text to compare...",
"algorithm": "combined",
"caseSensitive": false,
"ignoreWhitespace": true,
"minWordLength": 2
}
}
}有问题或反馈？请联系 [email protected]
| number |
| 否 |
| Ignore words shorter than this length |
文本结果
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}