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.

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Basic information
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.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"sentor": {
"command": "uvx",
"args": [
"sentor-mcp"
],
"env": {
"SENTOR_API_KEY": "<YOUR_API_KEY>"
}
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
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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