Headline Vibes Analysis MCP Server

Headline Vibes Analysis MCP Server

Analyzes sentiment in news headlines from major US publications using both standard and natural language date inputs, enabling insights into public sentiment trends.

fred-em

Research & Data
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Tools

analyze_headlines

Analyze sentiment of major news headlines using natural language date input

README

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

  • Node.js v16 or higher
  • NewsAPI key (get one at https://newsapi.org)

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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