Text Classifier — Topic Categories & Readability MCP配置与使用教程
io.smithery.axel-belfort.text-classifier · vlatest
Text classification API for AI agents. Classify text into topic categories with confidence scores, readability metrics (Flesch-Kincaid), and content type detection (article, review, email, code, etc.). Tools: text_classify_content. Use this for content routing, auto-tagging, spam detection, or organizing unstructured text. IMPORTANT: For sentiment analysis, use text_analyze_sentiment instead. Returns: {categories[], readability, contentType, confidence}. No API key required — x402 micropayment $0.005/call on Base L2.
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产品介绍
Text classification API for AI agents. Classify text into topic categories with confidence scores, readability metrics (Flesch-Kincaid), and content type detection (article, review, email, code, etc.). Tools: text_classify_content. Use this for content routing, auto-tagging, spam detection, or organizing unstructured text. IMPORTANT: For sentiment analysis, use text_analyze_sentiment instead. Returns: {categories[], readability, contentType, confidence}. No API key required — x402 micropayment $0.005/call on Base L2. Text Classifier — Topic Categories & Readability 是一个MCP Server，收录自 smithery。支持 streamable-http 传输。本页提供产品介绍、配置教程、安装命令与适用场景，可复制到 Cursor、Claude Code、VS Code。
按平台快速复制
选择你的平台查看安装方式
- 打开项目根目录下的 .cursor/mcp.json（没有就新建）
- 点击「复制配置」粘贴进去；若已有其他 MCP，只合并 mcpServers 里的本条目
- 保存后按 Cmd+Shift+P（Windows：Ctrl+Shift+P）→ 输入 Reload Window 并执行
{
"mcpServers": {
"io-smithery-axel-belfort-text-classifier": {
"url": "https://smithery.ai/servers/axel-belfort/text-classifier"
}
}
}