Sentiment Ninjas

Provides sentiment analysis by querying the Api Ninjas Sentiment API through an MCP server.

python

0

GitHub Stars

python

Language

4 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "bach-ai-tools-bachai-sentiment-by-api-ninjas": {
      "command": "python",
      "args": [
        "server.py"
      ],
      "env": {
        "API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

You can access sentiment analysis by Api Ninjas through this MCP server. It provides a simple, authenticated way to analyze text sentiment from your applications using a lightweight stdio-based MCP connection.

How to use

You connect to the Sentiment By Api Ninjas MCP server using an MCP client that supports stdio connections. Run the server locally and point your client to the provided stdio entry. The server exposes a sentiment analysis tool that returns a sentiment score and overall sentiment for a given block of text.

Key usage pattern: you authenticate with an API key, start the MCP server, and then call the v1sentiment tool with the text you want analyzed. The server handles the request to Api Ninjas and returns the analysis results to your client.

How to install

Prerequisites: Python is required to install and run the package. You will also use uvx to run the MCP server quickly, or you can run in development mode with Python directly.

Additional notes

This MCP server requires an API key for authenticating with Api Ninjas. You should provide the key as an environment variable named API_KEY when running the server. You can set this variable in your shell or within your MCP client configuration.

Available tools

v1sentiment

Returns sentiment analysis score and overall sentiment for a given block of text via the GET /v1/sentiment endpoint.