AI Tools
分析文本情感和情绪语调，详细分析正面、负面和中性情绪
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-sentiment-analyzer' \
-H 'Content-Type: application/json' \
-d '{"text":"输入要分析情感和情绪的文本...","analysisDepth":"detailed","emotionType":"general","language":"en","includeSuggestions":true,"includeStatistics":false,"exportFormat":"readable"}'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-sentiment-analyzer| 参数名 | 类型 | 必填 | 说明 |
|---|---|---|---|
| text | textarea | 是 | Enter any text - reviews, comments, messages, articles, or personal writing for sentiment analysis |
| analysisDepth | select | 是 | 选择情感分析的深度 |
| emotionType | select | 是 | 选择分析中要关注的情感类型 |
| language | select | 是 | 选择被分析文本的语言 |
| includeSuggestions | checkbox | 否 | 包含更好的情感理解和沟通建议 |
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-sentiment-analyzer": {
"name": "text-sentiment-analyzer",
"description": "分析文本情感和情绪语调，详细分析正面、负面和中性情绪",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=text-sentiment-analyzer",
"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-sentiment-analyzer",
"arguments": {
"text": "输入要分析情感和情绪的文本...",
"analysisDepth": "detailed",
"emotionType": "general",
"language": "en",
"includeSuggestions": true,
"includeStatistics": false,
"exportFormat": "readable"
}
}
}有问题或反馈？请联系 [email protected]
| includeStatistics |
| checkbox |
| 否 |
| 包含情感统计、百分比和数据可视化 |
| exportFormat | select | 否 | 选择分析输出的格式 |
流式结果
data: {"chunk": "data: processed content 1", "type": "stream"}
data: {"chunk": "data: processed content 2", "type": "stream"}
data: {"type": "done"}