Headline Vibes Analysis MCP Server

Headline Vibes Analysis MCP Server

By fred-em GitHub

MCP Server - get a heat check headlines

headline-vibes sentiment-analysis
Overview

what is Headline Vibes?

Headline Vibes is a Model Context Protocol server that analyzes sentiment in news headlines from major US publications, providing insights into the overall sentiment of news coverage.

how to use Headline Vibes?

To use Headline Vibes, clone the repository, install the dependencies, build the server, and configure your NewsAPI key. You can then analyze headlines using natural language date input or specific dates.

key features of Headline Vibes?

  • Analyzes up to 100 headlines per request
  • Sentiment scoring on a 0-10 scale (0 = most negative, 10 = most positive)
  • Natural language date parsing for easier input
  • Detailed source distribution information
  • Sample headlines included in results

use cases of Headline Vibes?

  1. Analyzing sentiment trends in news over time
  2. Comparing sentiment across different news sources
  3. Understanding public sentiment on specific events or topics

FAQ from Headline Vibes?

  • What is the maximum number of headlines that can be analyzed at once?

Up to 100 headlines can be analyzed per request.

  • Do I need an API key to use Headline Vibes?

Yes, you need a NewsAPI key to access the news headlines.

  • How does the sentiment scoring work?

The sentiment is scored on a scale from 0 to 10, where 0 indicates the most negative sentiment and 10 indicates the most positive.

Content

Headline Vibes Analysis MCP Server

A Model Context Protocol server that analyzes sentiment in news headlines from major US publications. The server provides both a standard date-based interface and natural language date parsing for easier use.

Features

  • Analyzes up to 100 headlines per request
  • Even distribution of headlines across major US news sources
  • Sentiment scoring on a 0-10 scale (0 = most negative, 10 = most positive)
  • Natural language date parsing (e.g., "yesterday", "last Friday")
  • Detailed source distribution information
  • Sample headlines included in results

Prerequisites

Installation

  1. Clone the repository:
git clone https://github.com/fred-em/headline-vibes.git
cd headline-vibes
  1. Install dependencies:
npm install
  1. Build the server:
npm run build
  1. Configure your NewsAPI key in your MCP settings file:
{
  "mcpServers": {
    "headline-vibes": {
      "command": "node",
      "args": ["/path/to/headline-vibes/build/index.mjs"],
      "env": {
        "NEWS_API_KEY": "your-api-key-here"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Available Tools

analyze_headlines

Analyze sentiment using natural language date input or specific dates.

Example usage:

// Using natural language
{
  "name": "analyze_headlines",
  "arguments": {
    "input": "yesterday"
  }
}

// Or using specific dates
{
  "name": "analyze_headlines",
  "arguments": {
    "input": "2025-02-11"
  }
}

Input examples:

  • "last Friday"
  • "3 days ago"
  • "March 10th"
  • "two weeks ago"
  • "2025-02-11" (YYYY-MM-DD format also supported)

Response Format

The tool returns results in the following format:

{
  "score": "6.50",              // Normalized sentiment score (0-10)
  "synopsis": "Overall positive sentiment in today's headlines",
  "headlines_analyzed": 100,    // Number of headlines analyzed
  "sources_analyzed": 12,       // Number of unique sources
  "source_distribution": {      // Distribution of headlines by source
    "Reuters": 10,
    "Associated Press": 8,
    "CNN": 9,
    // ... etc
  },
  "sample_headlines": [         // Up to 5 sample headlines
    "Example headline 1",
    "Example headline 2",
    // ... etc
  ]
}

News Sources

The server pulls headlines from major US news sources including:

  • Associated Press
  • Reuters
  • CNN
  • Fox News
  • NBC News
  • ABC News
  • Wall Street Journal
  • Washington Post
  • USA Today
  • Bloomberg
  • Business Insider
  • Time

Error Handling

The server provides clear error messages for common issues:

  • Invalid date formats
  • Unparseable natural language queries
  • No headlines found for the specified date
  • API errors from NewsAPI

Development

To run the server in watch mode during development:

npm run watch

License

MIT

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