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Headline Vibes Analysis MCP Server

Headline Vibes Analysis MCP Server

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github.com/fred-emFinance6Updated 16w ago

About Headline Vibes Analysis MCP Server

Headline Vibes is an MCP server for analyzing investor sentiment in US news headlines from EventRegistry. It supports daily and monthly reports with sentiment scores, source and political breakdowns, and sampling diagnostics.

Key features

  1. 01Daily and monthly headline analysis
  2. 02General and investor sentiment scores
  3. 03Political and source breakdowns
  4. 04Natural-language date input
  5. 05Structured results and diagnostics

Use cases

  1. 01Review investor sentiment for a specific day
  2. 02Compare headline trends across months
  3. 03Inspect political leaning and news sources

MCP support

Exposes `analyze_headlines` and `analyze_monthly_headlines` to MCP clients, returning structured headline analysis. It runs over stdio or HTTP.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Headline Vibes — EventRegistry MCP Server

Headline Vibes is a Model Context Protocol server that analyzes investor sentiment in US news headlines fetched from EventRegistry (newsapi.ai). It supports daily and monthly analysis modes, produces structured outputs with diagnostics, and runs over stdio or HTTP (Railway-ready).

Features

  • Curated US newsroom coverage with investor relevance filtering
  • Dual sentiment scores (general + investor) normalized to a 0–10 scale
  • Political-leaning breakdowns, source distributions, and sampling diagnostics
  • Natural-language date parsing for daily requests ("yesterday", "last Friday", etc.)
  • Structured JSON outputs compatible with MCP structuredContent
  • Built-in token budgeting and rate-limit telemetry

Prerequisites

Setup

  1. Install dependencies and build:
    npm install
    npm run build
    
  2. Configure environment variables (stdio example):
    {
      "mcpServers": {
        "headline-vibes": {
          "command": "node",
          "args": ["/absolute/path/headline-vibes/build/index.mjs"],
          "env": {
            "NEWS_API_KEY": "your-eventregistry-key",
            "TRANSPORT": "stdio"
          }
        }
      }
    }
    
  3. For HTTP (Railway) deployments, set TRANSPORT=http, HOST=0.0.0.0, PORT=<port>, and optionally ALLOWED_HOSTS/ALLOWED_ORIGINS.

Available Tools

analyze_headlines

Daily sentiment snapshot for a single day. Arguments: { "input": string }.

  • Accepts natural language or YYYY-MM-DD.
  • Returns investor/general scores, synopses, distributions, sample headlines, and diagnostics.
analyze_monthly_headlines

Monthly aggregation between two months. Arguments: { "startMonth": "YYYY-MM", "endMonth": "YYYY-MM" }.

  • Outputs per-month political sentiments, headline counts, and token/sampling diagnostics.

JSON schemas powering structured results live in src/schemas/headlines.ts.

Development & Testing

  • Watch mode: npm run watch
  • Stdio run: NEWS_API_KEY=... npm run start:stdio
  • HTTP run: TRANSPORT=http HOST=0.0.0.0 PORT=8787 NEWS_API_KEY=... npm run start:http
  • Smoke check EventRegistry connectivity: node ./build/scripts/smoke.mjs 2025-02-01
  • Unit tests (Vitest): npm test

Railway Deployment

  1. Set environment variables (TRANSPORT, HOST, PORT, NEWS_API_KEY, optional ALLOWED_HOSTS, ALLOWED_ORIGINS, LOG_LEVEL).
  2. Build once locally (npm run build) or via Railway’s build step.
  3. Start with npm run start.
  4. Health probe: GET /healthz returns 200 ok.

See docs/railway.md for the full playbook and docs/claude-desktop.md for Claude Desktop integration steps.

License

MIT

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