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Headline Vibes Analysis MCP Server: Crush Competitors, Sizzle Feeds 🔥 - MCP Implementation

Headline Vibes Analysis MCP Server: Crush Competitors, Sizzle Feeds 🔥

Headline Vibes Analysis MCP Server: Get that heat check—crush competition, dominate feeds, and hit with headlines that sizzle. 🔥

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About Headline Vibes Analysis MCP Server

What is Headline Vibes Analysis MCP Server: Crush Competitors, Sizzle Feeds 🔥?

Headline Vibes Analysis is a purpose-built MCP server designed to dissect sentiment trends in US news headlines. By aggregating content from major publications like Reuters, CNN, and the Wall Street Journal, it delivers actionable sentiment scores (0-10) that help users quickly gauge public perception. Its unique blend of natural language date parsing and standardized API access ensures seamless integration for competitive analysis.

How to Use Headline Vibes Analysis MCP Server: Crush Competitors, Sizzle Feeds 🔥?

  1. Install dependencies via npm and configure your NewsAPI key
  2. Deploy the server using the provided MCP configuration template
  3. Query sentiment data using date ranges like "last Friday" or ISO dates
  4. Interpret results through standardized JSON responses showing sentiment scores, source distribution, and sample headlines

Headline Vibes Analysis MCP Server Features

Key Features of Headline Vibes Analysis MCP Server: Crush Competitors, Sizzle Feeds 🔥?

  • Sentiment Precision: 0-10 scoring with 0.25 increments
  • Source Coverage: Balanced aggregation from 12+ major US news outlets
  • Flexible Querying: Natural language ("3 days ago") or ISO date format
  • Transparency: Source distribution breakdown and headline samples
  • Error Resilience: Clear diagnostics for API issues or invalid queries

Use Cases of Headline Vibes Analysis MCP Server: Crush Competitors, Sizzle Feeds 🔥?

Business analysts use it to:

  • Monitor brand reputation through media sentiment trends
  • Identify emerging news cycles affecting stock markets
  • Competitor benchmarking by comparing industry-specific coverage
  • Validate PR campaigns against real-time media reaction

Headline Vibes Analysis MCP Server FAQ

FAQ from Headline Vibes Analysis MCP Server: Crush Competitors, Sizzle Feeds 🔥?

  • Q: How many headlines are analyzed per query?
    A: Up to 100 headlines per request, balanced across sources
  • Q: What dates are supported?
    A: Any date within API provider's archive (typically last 30 days)
  • Q: Can I customize scoring?
    A: Scoring algorithm is fixed for consistency but outputs include raw data points
  • Q: What happens if sources are unavailable?
    A: Returns partial results with detailed error codes for missing sources

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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