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.
git clone https://github.com/fred-em/headline-vibes.git
cd headline-vibes
npm install
npm run build
{
"mcpServers": {
"headline-vibes": {
"command": "node",
"args": ["/path/to/headline-vibes/build/index.mjs"],
"env": {
"NEWS_API_KEY": "your-api-key-here"
},
"disabled": false,
"autoApprove": []
}
}
}
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:
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
]
}
The server pulls headlines from major US news sources including:
The server provides clear error messages for common issues:
To run the server in watch mode during development:
npm run watch
MIT
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