What does Sentor do that a general sentiment API doesn’t?
Sentor performs entity-based sentiment analysis: it scores sentiment toward specific entities (e.g., a brand or feature) rather than providing an overall document sentiment.

@NIKX-Tech
基本信息
Stop guessing why ratings drop. Give your AI assistant Sentor and let it analyse thousands of reviews, pinpoint what to fix first, and surface the topics that matter most.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"sentor": {
"command": "uvx",
"args": [
"sentor-mcp"
],
"env": {
"SENTOR_API_KEY": "<YOUR_API_KEY>"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
Sentor is an entity-based sentiment analysis platform powered by fine-tuned BERT models. This MCP server exposes Sentor’s ML APIs as tools that AI assistants can call directly for sentiment scoring, topic clustering, and label generation.
Install using uvx sentor-mcp — no server to run, no infrastructure needed. Obtain a free API key at dashboard.sentor.app and configure the server to use it.
Sentor performs entity-based sentiment analysis: it scores sentiment toward specific entities (e.g., a brand or feature) rather than providing an overall document sentiment.
No server to run or infrastructure to manage. Install via `uvx sentor-mcp` and provide an API key.
Sentor processes text through its cloud-based ML APIs. Documents and results are handled on Sentor’s servers per their data policy (not detailed further in this README).
The MCP server communicates with Sentor’s APIs over standard HTTP (not specified in README beyond API key usage; typical MCP transport is stdio or HTTP).
Get a free API key at [dashboard.sentor.app](https://dashboard.sentor.app/settings?tab=api-access) and provide it when configuring the MCP server.
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