Helium MCP Server

Real-time news with bias scoring, live market data, and AI-powered options pricing — all accessible through the Model Context Protocol.

Overview

Helium MCP gives your AI assistant access to:

• 3.2M+ news articles from 5,000+ sources, each scored across 15+ bias dimensions
• Balanced news synthesis — left, right, and center perspectives aggregated into one coherent story
• Live market data — price, IV rank, AI-generated bull/bear cases, and price forecasts
• AI options pricing — proprietary ML models for fair-value estimates and probability ITM
• Meme search — semantic search across viral memes with OCR text and captions

50 free queries included. No sign-up required.

Quick Start

Cursor

Add to your Cursor MCP settings:

{
  "mcpServers": {
    "helium": {
      "url": "https://heliumtrades.com/mcp"
    }
  }
}

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "helium": {
      "type": "streamable-http",
      "url": "https://heliumtrades.com/mcp"
    }
  }
}

Windsurf

Add to your Windsurf MCP settings:

{
  "mcpServers": {
    "helium": {
      "serverUrl": "https://heliumtrades.com/mcp"
    }
  }
}

GitHub Copilot

Add to your .github/copilot-instructions.md or MCP config:

{
  "mcpServers": {
    "helium": {
      "type": "streamable-http",
      "url": "https://heliumtrades.com/mcp"
    }
  }
}

Any MCP Client

Connect to the streamable HTTP endpoint:

https://heliumtrades.com/mcp

Example Output

"What's the bull and bear case for Bitcoin?"

get_ticker("BTC")
→ Bitcoin: $71,040.01
  Bull case: "Institutional spot demand resumes... squeeze toward mid/upper-80ks to low-100ks"
  Bear case: "Higher-for-longer rates, persistent ETF outflows... slide into 40–55k plausible"
  Forecast: +1.8% over 37 days (range: -1.2% to +5.0%)
  IV Rank: available
  Options strategies: long vol + short vol packs included

"How biased is CNN?"

get_source_bias("CNN")
→ Emotionality: 7/10
  30+ bias dimensions scored (political lean, fearfulness, opinion, oversimplification...)
  Signature phrases: "trump threatens", "mortgage rates", "nuclear weapons"
  Similar sources: NBC, PBS, AP, Newsweek, CBS
  Per-article bias breakdown on recent stories included

"What are the best options trades right now?"

get_top_trading_strategies()
→ AI-ranked short vol + long vol setups
  Each includes: ticker, price, bull/bear case, 5 probability-weighted outcomes,
  full option pack (strike, expiry, Greeks, ML fair value, probability ITM)

"Give me NVIDIA's full analysis"

get_ticker("NVDA")
→ NVIDIA: $183.91
  5 probability-weighted scenarios (38% mean-revert, 25% +10-25%, 20% -5-12%...)
  Forecast: +4.2% over 37 days (range: -2.6% to +8.9%)
  IV rank, volatility surface, term structure, return profile charts
  27 time-horizon uncertainty visualizations (1-day to 995-day)

"Find me stock market crash memes"

search_memes("stock market crash")
→ Babylon Bee: "Kamala Desperately Googles 'What Is A Stock Market Crash'" (32K likes)
→ "Everyone: 'omg the stock market is crashing!' / 500 cigarettes adapter" (437K likes)
  Full OCR text, source, date, image URLs included

Tools

search_news

Full-text search across 3.2M+ articles from 5,000+ sources. Filter by source, category, date, and minimum shares. Returns bias scores, AI summaries, and context.

Parameters:

search_balanced_news

AI-synthesized articles that aggregate multiple sources into balanced coverage. Each story includes a summary, takeaway, evidence breakdown, potential outcomes, and relevant tickers.

Parameters:

get_source_bias

Deep bias analysis for any news outlet: political lean, emotional tone, prescriptiveness, signature phrases, similar sources, and historical trends.

Parameters:

get_bias_from_url

Analyze any article URL for per-dimension bias scores: political lean, emotionality, manipulation level, factfulness, and more.

Parameters:

get_ticker

Comprehensive data for any stock, ETF, or crypto: live price, AI-generated bull/bear cases, price forecast, IV rank, volatility surface, and top-ranked options strategies.

Parameters:

get_option_price

Helium's proprietary ML model-predicted fair-value price for a specific option contract. Returns predicted price, probability ITM, and the data date.

Parameters:

get_top_trading_strategies

Helium's highest-conviction options setups ranked by AI edge score, expected value, and market conditions. Returns both short volatility and long volatility strategies.

Parameters:

get_all_source_biases

Bias scores for every tracked news source — compare outlets, rank by credibility, or build a full media landscape overview. Returns all sources with >100 articles analyzed, sorted by average social shares.

Parameters: None required.

search_memes

Semantic search across viral memes — images, captions, OCR text, like counts, and source attribution.

Parameters:

Pricing

Get an API key at heliumtrades.com/mcp-page.

Examples & Recipes

Want to see each endpoint used in real Python workflows? The helium-mcp-cookbook repo contains six short, runnable recipes covering news-bias ranking, options calibration tracking, balanced-news synthesis, source credibility ranking, ticker forecasts, and top-strategies. Each is a single file you can run with python recipes/NN_name.py.

Links

• Helium MCP Page
• helium-mcp-cookbook — six runnable Python recipes
• Glama
• Smithery
• npm
• Helium Trades
• Privacy Policy

License

MIT